Disrupting Hollywood Paradigms with Analytics

At the April 4th L.A. Marketing Analytics Group, Matt Marolda, Chief Analytics Office at Legendary Entertainment presented on Disrupting Hollywood Paradigms with Analytics. We were treated with some very interesting and thought provoking innovations that Matt and his team at Legendary Entertainment are working on to uncover powerful insights about mainstream box office audiences in the US and worldwide. This insightful information helps inform marketing tactics and overall production investment strategies.

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On April 4th, we had the pleasure of hosting Matt Marolda, Chief Analytics Officer with Legendary Entertainment at the monthly L.A. Marketing Analytics Group.  The event is hosted by eSage Group.

At our event, Matt presented on Disrupting Hollywood Paradigms with Analytics.  We were treated with some very interesting and thought provoking innovations that Matt and his team at Legendary Entertainment are working on to uncover powerful insights about mainstream box office audiences in the US and worldwide.  This insightful information helps inform marketing tactics and overall production investment strategies.

side bar for mayMatt and his Applied Analytics team are tasked with informing several key components of the movie making and marketing process.

The following is a list of the key discussion points and learnings from Matt’s presentation.

  • Informing Creative: Evaluate movie concepts, cast, themes and fan base long before a single dollar is spent on movie production.
  • Transforming Marketing: Use analytics to identify, understand, reach, and persuade individuals to watch a particular movie.
  • Understanding People, Content, Social and Conversation: Create a virtuous feedback loop where these four inputs are integrated into the overall marketing process to provide a continuously improving understanding of your audience over time.
  • Identify Varying Degrees of Persuadable People: Identify three clusters of persuadable personas with varying degrees of predictability with regards to convincing them to attend a particular movie.
  • Innovative Experimentation that Yields Big Wins: Movies that aren’t positively received in one part of the world may perform well in other regions. Use experimentation to test market acceptance of a particular movie in other regions before making further marketing investments.

Read on to hear more about how Matt and his team are shaking apart the old Hollywood Paradigms and creating a truly data-driven movie making environment at Legendary.


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Olegendary grey logo.pngn April 4th, at the monthly L.A. Marketing Analytics Group which is hosted by eSage Group, we had the pleasure of hosting Matt Marolda, Chief Analytics Officer at Legendary Entertainment. At the event, Matt presented on Disrupting Hollywood Paradigms with Analytics and we were treated with some very interesting and thought provoking innovations that Matt and his team are working on at Legendary to uncover insights about the mainstream box office audience in the US and worldwide.

It is known that Hollywood has many marketing paradigms that have been well entrenched for decades, some good, others beg to be disrupted. One of those stale marketing tenets that are being reevaluated and shifted to something more useful is how Hollywood has been segmenting the market using the often cited four quadrants: by male, female, over 25, and under 25; totaling 4 groups of 80 million people in the US, which is probably one of the crudest ways to look at the marketplace. Legendary is changing this old practice by looking at ways to see an audience in a much more granular way by micro segmenting this model into 80 million groups of 4, give or take – which seems daunting. But if you consider the top down leadership effort at Legendary to drive a culture of data driven marketing, it becomes more realistic. Two key efforts at Legendary that Matt and his team have been driving include Informing Creative and Transforming Marketing through applied analytics.

Informing Creative: All movie studios must decide on what creative movie concept, cast, and theme should be green-lighted, and which fan base should be targeted long before a single dollar is spent on making the movie. For much of the entertainment industry’s history scripts have been written and submitted, discussed and debated, picked up and dropped. This process includes top level executives deciding on whether the movie is going to be viable, profitable, and on brand for the studio.

Many of those decisions in the past were made by gut instinct, and then hope, prayer, chanting and the burning of incense was involved (at least in my version of this). With the advent of data collection and analytics being injected into the creative decision process, decision makers are shifting to a more data-driven approach when deciding to make a film. Present day studio brass at Legendary are now utilizing analytics (by way of Matt’s Applied Analytics Team) to evaluate movie concepts, the cast, screen fans ahead of time, test the theme, and they even look at sequel viability in order to inform the creative process and uncover the potential ROI in a very predictive way. This includes looking deeply at People, Content, Social and Conversation which I’ll talk more about in a bit. Legendary Entertainment CEO and visionary, Thomas Tull sought a better way when he launched the company in 2000.  As of 2017 Tull is no longer CEO, but his decision to hire Matt Marolda in 2013 to take Money Ball to Hollywood remains firmly intact.

Transform Marketing: Legendary shifted to an internal analytics team tasked with altering the marketing process from an older model sadly referred to as spray and pray where marketing dollars are spent in volume to reach all people with the hope that they will show up at box office. The paradigm shift is towards a more targeted approach that seeks to identify, understand, reach, and persuade individuals. Beyond that goal is the effort to reduce marketing spend by 20% through the strategic targeting of specific audience segments. That reduction in marketing spend directly affects the bottom line of movies on a global scale. Legendary is doing this is by maintaining an analytics team comprised of three groups: The Quantitative Group, The Development Group and the Delivery Group.

It’s the Quantitative team’s job to tap tons of data and apply it to the movie making and marketing processes directly using analytics. The Development team is tasked with integrating complex data feeds rapidly, turning the models of the Quant team into software, building high speed querying to allow iteration and refinement, and launching media feeds through API’s.  Finally, it is the Delivery team’s job to execute media buys on all digital platforms, where for Legendary, media agencies were unable to deliver at the speed and scale that is required to be competitive in this fast-moving effort to turn insights into marketing action that targets segments uncovered earlier in this process.

Successful marketing analytics teams everywhere strive to experiment, learn, “fail” fast, and reiterate the ongoing process in an unending feedback loop. This agile approach to data driven marketing continues to prove that trying things that might have failed in the past, or those that weren’t ever tried, can still yield big wins. This “panning for gold” approach either yields an answer confirming that one consumer messaging approach or another did not work, or in other cases it is uncovering novel and successful messaging that would not have been conceived of otherwise. Therein lies the paradigm shift from overspending and gut instinct marketing on a grand scale, to the highly targeted and strategic approach that not only saves marketing dollars, but imparts analytics that allow organizations to make their current marketing spend far more productive.

side bar for mayPeople, Content, Social & Conversation Looking at how competitive and successful movie companies like Legendary Entertainment approach data collection and the insights that are surfaced is a great example of how to stay competitive in any marketplace. This innovative approach to analytics is apparent in Matt’s Applied Analytics team who uses a virtuous cycle where four specific areas of data are integrated in unique ways. They collect and analyze information on People, Social, Content, and Conversation.

 

  • People Information: Includes 1.5 billion email addresses, 200 million households with PII (Personally Identifiable information) and hundreds of other attributes per person sourced from a multitude of available data. The Applied Analytics team at Legendary has curated this data set internally to enable them to identify, reach, understand, and persuade people.
  • Content Information: Includes box office data by individual theater for all movies from 2007, all US based advertising since 2007, meta data by second for movies from the 80’s to present day that identify actors in each scene, topic of conversation, tone & tenor of background music. These pieces of information are all crucial for comp’ing and modeling in the property evaluation process – which determines properties to buy, which movies to make, and which actors will be in them.
  • Social Media Information: Includes feeds from 500 million Twitter profiles and billions of tweets, 100 million Facebook profiles, all of Reddit, all of Wikipedia, plus thousands of News Sites and Blogs are scoured, collected and stored for insights.
  • Conversation Information: Includes social interactions by geography, plus extensive analysis on text and images using traditional and innovative techniques to help inform movie makers and marketers. This data helps Legendary understand current trends, what people are saying about particular movies along with their associated sentiment.

Using tools to analyze People, Content, Social and Conversation have helped Legendary build audience profiles and create hundreds of microsegments, identify key persuadable points and produce detailed, actionable insights. Acting on this data by matching profiles to key aspects of a movie surfaced from movie meta data informs Legendary on what movie to promote and to which persuadable audience. Changes of intent are also measured and creative actionable insights emerge at a rate of over 50 per movie, per week. This analytics ecosystem which integrates data, analytics, and campaigns, along with deep API integration allows for scale execution, sophisticated reporting and continual optimization.

Varying Degrees of Persuadable People: When Trying to identify persuadable sets of personas, Legendary looks at three clusters of people who hold varying degrees of predictability with respect to the ability to convince them to attend a particular movie.

First, there are folks that have been engaging with a property since childhood. Movies like Godzilla, King Kong and Warcraft have a historically long-standing culture of followers. Legendary seeks to turn those people into active evangelists. Marketing to them does not require a high-dollar spend because of their inherent affinity for the subject matter. Simply advertising key points like hints at trailers to be dropped and the dates of movie release are all that this group needs. The marketing effort is just to “stoke the flame” for this group.

Another cluster of people is identified as the “your mom” segment.  With this segment Legendary understands that there are just certain movies that they will not attend.  So there is no need to spend marketing dollars on this group when marketing a certain genre of movies.  Legendary will save these marketing dollars for other groups that are more apt to engage.

The third identifiable cluster is defined as the “people in the middle.” This group, when served the right creative at the right time will change their mind and their opinion of the film. In May of 2014 Legendary ran some testing on the Godzilla release. They found, unexpectedly that women ages 24 to 36 were identified as persuadable. This was a key insight. Legendary didn’t think this segment would be a viable target when they were whiteboarding their marketing effort. They then used analytics to design the movie trailer through insights uncovered about this new segment. The insights uncovered showed them that they needed to emphasize the conspiracy theory in the Godzilla plot rather than the monster destroying the city. They also knew to emphasize Bryan Cranston who was fresh off Breaking Bad. The trailer they created resonated with women and they subsequently launched an extensive marketing campaign around this knowledge, while continuing to further optimize their marketing for these segments.  Uncovering surprising and unexplainable segments like this has proven to be extremely valuable.  Establishing a culture of experimentation and building feedback loops into your strategy allows for these kinds of powerful insights.  Once a new segment is identified, predictive models are built to identify who is likely to engage with particular content.  With propensity scores, Legendary can zero in on targets as they get closer to the release, whereas other studios tend to get more panicked and market to a broader audience.  Legendary can go narrower, targeting only the specific people they think will act to a particular marketing piece.  When thinking of the world on a more CPM basis this is a better way to go.  Plus, this can all be done at scale.  This same process works for blockbuster films or much smaller projects, with both receiving lift.  With this lather, rinse and repeat methodology, these efforts all continue to inform and allow for continual optimization. Data is collected on an ongoing basis and appended back into the database, so the system continuously learns what approaches work and which don’t.  The system is continuously getting smarter and providing ever greater ROI over time.

A Third Paradigm Shift: A third and final example of how Legendary is disrupting the old Hollywood paradigms can be seen in their effort around the release of Warcraft. The movie was tested in China, with data being collected on 8 different versions of the movie with hundreds of test subjects using biometric Fitbit-like devices to track heart rate, blood pressure, oxygen levels, and more. Also, iPad-like devices were used to capture facial expressions during the viewings.  These experiments provided information on how viewers were engaged with the movie in several ways.

This data ultimately revealed that a movie that was “panned” by the critics and dubbed awful in the United States would in fact resonate well with the Chinese audience.  The movie was launched globally and was a box office success in China grossing over $220 million.  This was a record in this geo and the movie ended up with total global revenue of over $433 million.

In Closing:  The analytics concepts being harnessed by the team at Legendary are innovative and cutting edge and might just prove to Hollywood once and for all that analytics are here to stay and not just a passing fad as some have said (as they were packing up their belongings and seeking a new line of work).  Those of us who seek deeper knowledge of our customers and processes in business know that if you aren’t competing with analytics, you’re not competition.

Many of the efforts at Legendary are reminiscent of the work we do at eSage Group. For large entertainment companies and several other verticals, we too help our customers obtain deeper insights through data integration and analytics. If your marketing organization is looking to migrate from the Spray and Pray digital marketing approach to a modern and efficient Marketing BI/Analytics infrastructure, we at eSage Group can assist in that process in a myriad of ways.  We help our clients integrate data from a multitude of various sales, marketing, partner and social channels, no matter the format of the data or the system it’s sourced from.  We design and build Marketing Analytics Data Warehouses, Data Lakes, Data Marts and connect newly integrated data to all your favorite reporting and analytics tools.  We are equally comfortable with on-prem and cloud based traditional data warehouse technologies such as Microsoft SQL Server, as well as most of the modern Big Data/Hadoop based platforms.

Our goal at eSage Group is to assure that marketing teams are obtaining useful and highly actionable insights from all internal and externally collected sales and marketing data. For more information on eSage Group and how we help our clients, please visit our website or email me directly.

The Future of Enterprise Analytics

Over the last couple weeks since the 2016 Hadoop Summit in San Jose, eSage Group has been discussing the future of big data and enterprise analytics.  Quick note – Data is data and data is produced by everything, thus big data is really no longer an important term.

hspeopleeSage Group is specifically focused on the tidal wave of sales and marketing data that is being collected across all channels, to name a few:

  • Websites – Cross multiple sites, Clicks, Pathing, Unstructured web logs, Blogs
  • SEO –  Search Engine, Keywords, Placement, URL Structure, Website Optimization
  • Digital Advertising – Format, Placement, Size, Network
  • Social
    • Facebook – Multiple pages, Format (Video, Picture, GIF), Likes (now with emojis), Comments, Shares, Events, Promoted, Platform (mobile, tablet, PC) and now Facebook Live
    • Instagram – Picture vs Video, Follows, Likes, Comments, Reposts (via 3rd Party apps), LiketoKnow.it, Hashtags, Platform
    • Twitter – Likes, RT, Quoted RT, Promoted, Hashtags, Platform
    • SnapChat – Follows, Unique views, Story completions, Screenshots.  SnapChat to say the least is still the wild west as to what brands can do to engage and ultimately drive behavior.

Then we have Off-Line (Print, TV, Events,  etc). Partners. 3rd Party DataDon’t get me started on International Data. 

Tired yet?

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While sales and marketing organizations see the value of analytics, they are hindered by what is accessible from the agencies they work with and by the difficulty of accessing internal siloed data stored across functions within the marketing organization – this includes central corporate marketing, divisional/product groups, field marketing, product planning, market research and operations.

Marketers are hindered by access to the data and the simple issue of not knowing what data is being collected.  Wherever the data lies, it is often controlled by a few select people that service the marketers and don’t necessary know the value of the data they have collected.  Self-service and exploration is not possible yet.

Layer on top this the fact that agile marketing campaigns require real-time data (at least close real time) and accurate attribution/predictive analytics.

So, you can see there are a lot of challenges that face a marketing team, let alone the deployment of an enterprise analytics platform that can service the whole organization.

Now that I have outlined the business challenges, let’s look at what technologies were mentioned at the 2016 Hadoop Summit that are being developed to solve some of these issues.

  • Cloud, cloud, cloud– lots of data can be sent up, then actively used or sent to cold storage on or off prem.  All the big guys have the “best” cloud platform
  • Security – divisional and function roles, organization position, workflow
  • Self-Service tools – ease of data exploration, visualization, costs
  • Machine Learning and other predictive tools
  • Spark
  • Better technical tools to work with Hadoop, other analytics tools and data stores
  • And much more!  

Next post, we will focus on the technical challenges and tools that the eSage Group team is excited about.

Cheers! Tina

 

 

 

Get Marketing Insights Fast Without a Data Hostage Crisis

shutterstock_210349615The landscape for marketing analytics solutions is more cluttered than ever with multiple options and approaches for marketing departments to consider.  One option that we are seeing more and more of is a seductive offering that promises a simple, fast, nearly turnkey approach to getting analysis and insight from your growing stacks of data.  The offer is this: a vendor will import your data to their systems, do analysis on it with their in-house experts, and come back to you with insights that will help you run your business better.

No doubt, this is an attractive offer if you are like many marketing organizations, struggling to get internal resources to help consolidate data and do the analysis required to get you the insights you need.   Business Intelligence resources are hard to find in your company, the data holders in IT are backlogged and short staffed.  You need insights now to help engage and sell to your customers and are done waiting on internal resources so why not go this route?  While likely a quick, tactical solution that will get you answers in the near term, there are several major drawbacks to this solution as a longer term strategy.

Market leading organizations know that their data is a significant asset that, when used well, can help them better understand and engage their customers, anticipate customer needs, cross sell, upsell, and stay ahead of the competition. As part of making data a core competency, your organization has to do the hard work to intimately know its data, its strengths, its shortcomings, and understand what it can tell you about your business.  That intimate understanding of data only comes from digging in, “doing the homework,” investing in the infrastructure and skillsets to excel at business intelligence inside the organization.  Organizations that have this kind of understanding of their data are continually improving the quality of data in their organization and building the kind of sustainable internal BI capability that actually adds significantly to the value and sustainability of the company.  C-suite, take note!

If you outsource that knowledge, you may get the answers you seek fast, but you do not get the sustainable, growing capability in-house that becomes a core differentiator for your company and helps you lead the market. datahostagecalloutI’m amazed when I hear this but it is very common practice. What if your vendor company goes out of business, gets acquired, changes business models or you decide to change vendors?  Your vendor is holding your data hostage.  What are you left with then?  All the money you spent bought you yesterday’s insights but you have no investment or capability towards the future.   Your team has none of the knowledge or infrastructure to sustain and continue to grow that flow of business intelligence that is critical to serving your customers and staying ahead of your competition.   You are back to zero.

Fair enough you say, but damn it, I still need insights now and I can’t wait any longer.  Tactical and non-sustainable is better than nothing right?  Well consider that it doesn’t have to be an “all or nothing” approach.  There is a way to get fast and sustainable.  You can start with a partner who gets you to the critical insights you need now, but is doing it on your systems, building out infrastructure you own (be it in the cloud on your behalf or on premises), and is helping mentor your team members along the way.  You may spend a little more along the way to do this, but in this approach you are investing, not just paying a monthly fee with no incremental addition of value to your company.  Very quickly you will be way ahead.

If the vendor you pick, in this case, goes out of business, moves on, or you decide to part ways, there may be some short term pain, but you own the assets, data, and business logic they built and you have team members who have been working directly with the technology and data, “doing the homework”, and can keep you moving forward.  Nobody has your data held hostage.

The right choice for a vendor should:

  • Have deep experience utilizing the cloud to get you up and running fast, with limited need for hardware purchase and support.  The cloud is great but make sure it is your, cloud, not someone else’s.
  • Work with you to understand your unique needs, data, internal team skills and challenges, and creates a roadmap to Business Intelligence ROI internally.
  • Provide all the senior BI talent you need now to get answers fast, but also help you grow that skill in house, with training, new employee interviewing and ongoing mentoring.  They need to have a demonstrated understanding that knowledge transition to your team is part of the deliverable and be committed to providing it.

Pick a partner who can help you avoid having your data taken hostage, while getting you the insights and ROI you need fast!

Written by Duane Bedard, eSage Group President and Co-Founder

 

 

Executive Evening Out with eSage Group and Microsoft

On March 10th, eSage Group held its first Executive Evening Out at the exclusive Rainier Club in Downtown Seattle. The event was sponsored by Microsoft Advanced Analytics.

On March 10th, eSage Group held its first Executive Evening Out at the exclusive Rainier Club in Downtown Seattle.  The event was sponsored by Microsoft Advanced Analytics.

15 Seattle area executives, from the likes of Starbucks, Trupanion, Allrecipes, Alaska Air, Disney and their guests joined us for a short presentation by Shish Shridhar, Worldwide Director for Business Intelligence Solutions – Retail for Microsoft, then sat down to a 5 course meal with wine pairings presented by The Rainier Club sommelier.

Microsoft has a powerful offering, from Azure Machine Learning, Cortana Analytics Suite, SQL 2016 and PowerBI. It was definitely a learning experience along with a wonderful meal and wines.

 

A Year in Review – LA and Seattle MeetUps

It was quite a year for both the LA and Seattle Marketing Analytic MeetUps! We had terrific speakers share on current topics! In LA, we had Nevious Osborne of Beats by Dre talking effective dashboards, Peter Taylor of Belkin talking IoT analytics and Punnoose Isaac of Edmunds.com talking on how to build an analytics infrastructure, just to name a few!  Check out the full list here.

Not to be outdone, Seattle had Jeremy Boore of Expedia talk Storytelling and Analytics, Chris Proser of Adobe talk about going beyond A/B testing, Kyle Wieranga of Costco talk on moving from Predictive to Prescriptive Analytics, Shish Shirdar from Microsoft talk Machine Learning, and Ed Mabanglo from Nordstrom talk time-to-event analysis to measure customer tenure. Check out the full list here.

2016 is proving to be great with Tania Massad from Mattel presenting in LA and Brian Behuin from Alaska Air presenting in Seattle.

Make sure to become a member for the Seattle and/or LA Marketing Analytic MeetUps to receive notices of upcoming events!

 

 

 

Understanding and Influencing the Customer Journey

Last week in Downtown LA, eSage Group and Microsoft hosted an Executive Learning Lounge focused on understanding and influencing the customer journey.

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The concept is a complex one. I came across this great article in the November issue of Harvard Business Review.  I hope you find it as insightful as I did.

If you are in Seattle, we are having a Customer Journey panel at the DAA Seattle Symposium on November 12th.  Shish Shirdhar will once again get in the panelist chair along with Michael Lisin of Disney and Duane Bedard of eSage Group will moderate!

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Competing on the Customer Journey – HBR, November 2015 – Executive Summary

As digital technology has enabled shoppers to easily research and buy products online, sellers have been scrambling after them, trying to understand and satisfy their wants. Savvy companies, however, are using new tools, processes, and organizational structures to proactively lead digital customers from consideration to purchase and beyond. They are creating compelling customer journeys and managing them like any other product—and gaining a source of competitive advantage.

Building successful journeys requires four key capabilities: automation, to smoothly carry customers through each step of their online path; personalization, to create a customized experience for each individual; contextual interaction, to engage customers and appropriately sequence the steps they take; and journey innovation, to add improvements that enhance and extend the journey and foster customer loyalty.

In addition, the most successful companies have a particular organizational structure, with a chief experience officer overseeing a journey-focused strategist and a “journey product manager.” This latter role is critical—the journey product manager leads a team of designers, developers, data analysts, marketers, and others to create and sustain superior journeys, and he or she is accountable for the journey’s ROI and general business performance.

Seeking 4 mid/senior level engineers to work on a Cloud-based Big Data project

eSage Group is always on the lookout for talented developers at all levels.  We have worked hard to create a company culture of sharp, quick learning, hardworking professionals who enjoy being part of a winning team with high expectations.   As such, we hire self-motivated people with excellent technical abilities who also exhibit keen business acumen and a drive for customer satisfaction and solving our client’s business challenges.   We have quarterly profit sharing based on companywide goals, allowing everyone on the team to participate in and enjoy the rewards of our careful but consistently strong growth. We are currently looking to fill 4 openings to complete a team that will be working together on a large-scale “big data” deployment on AWS.

  1. Cloud-operations specialist who can design a distributed platform for analyzing terabytes of data using MapReduce, Hive, and Spark.
  2. Cloud-database engineer who can construct an enterprise caliber database architecture and schema for a high-performance Cloud-based platform that stores terabytes of data from several heterogeneous data sources.
  3. Mid/senior-level software developer with extensive experience in Java, who can write and deploy a variety of data processing algorithms using Hadoop.
  4. A technical business analyst who can translate business requirements into user stories and envision them through Tableau charts/reports.

1) Cloud-operations specialist: • Bachelor’s degree in Computer Science or related field; or, 4 years of IT work experience • Familiarity with open-source programming environments and tools (e.g., ant, maven, Eclipse) • Comfortable using the Linux operating system, and familiarity with command-line tools (e.g., awk, sed, grep, scp, ssh). • Experience working with Web/Cloud-based systems (e.g., AWS, REST) • Knowledge of database concepts, specifically, SQL syntax • Data warehouse architecture, modeling, profiling and integration experience • Comfortable using the command line (e.g., Bash), experience with systems deployment and maintenance (e.g., cron job scheduling, iptables) • Practical work experience designing and deploying large-scale Cloud-based solutions on AWS using EC2, EBS, and S3 • Working knowledge of one or more scripting languages (e.g., Perl, Python) • Experience using systems management infrastructure (e.g., LDAP, Kerberos, Active Directory) and deployment software (e.g., Puppet, Chef) • Programming ability in an OOP language (e.g., Java, C#, C++) is a plus 2) Cloud-database engineer: • Bachelor’s degree in Computer Science or related field; or, 4 years of IT work experience • Familiarity with open-source programming environments and tools (e.g., ant, maven, Eclipse) • Comfortable using the Linux operating system, and familiarity with command-line tools (e.g., awk, sed, grep, scp, ssh). • Experience working with Web/Cloud-based systems (e.g., AWS, REST) • Knowledge of database concepts, specifically, SQL syntax • Firm grasp of databases and distributed systems; expert knowledge of SQL (i.e., indexes, stored procedures, views, joins, SISS) • Extensive experience envisioning, designing, and deploying large-scale database systems both in traditional computational environments and in the Cloud • Ability to design complex data ETLs and database schemas • Desire to work with many heterogeneous terabyte-scale datasets to identify and extract Business Intelligence • Experience using multiple DBMS (e.g., MySQL, PostgreSQL, Oracle, SQL Server) • Work experience using Hive and NOSQL databases is a plus 3) Mid/senior-level software developer: • Bachelor’s degree in Computer Science or related field; or, 4 years of IT work experience • Familiarity with open-source programming environments and tools (e.g., ant, maven, Eclipse) • Comfortable using the Linux operating system, and familiarity with command-line tools (e.g., awk, sed, grep, scp, ssh). • Experience working with Web/Cloud-based systems (e.g., AWS, REST) • Knowledge of database concepts, specifically, SQL syntax • Excellent Java developer with knowledge of software design practices (e.g., OOP, design patterns) who writes sustainable programs and employs coding best practices • Ability to program, build, troubleshoot, and optimize new or existing Java programs • Several years development experience using both version control (e.g., SVN, Git) and build management systems (e.g., Ant, Maven) • Able to create and debug programs both within IDE environments and also on the command line • Working knowledge of Web development frameworks and distributed systems (e.g., Spring, REST APIs) • Experience using Hadoop ecosystem (e.g., MapReduce, Hive, Pig, Shark, Spark, Tez) to program, build, and deploy distributed data processing jobs • Programming ability in Scala is a plus 4) Technical Business Analyst: • Strong background in business intelligence • Minimum of 1 year using Tableau and Tableau server. • Able to work closely with cross-functional business groups to define reporting requirements and use-cases • Extensive experience manipulating data (e.g., data cubes, pivot tables, SSIS) • Passion for creating insight out of data and data investigation • Experience using R, Mahout, or Matlab is a plus Please send resumes to tinam (at) esagegroup (dot) com