Manager, Data Analysis & Profiling

This is a Full Time Job

Manager, Data Analysis & Profiling

Manger, Data Analysis and Profiling, Audience Analytics and Activation represents an exciting new role at Sony Pictures Entertainment (SPE), positioned at the fast-moving intersection of film marketing strategy, digital ad tech, and big data / predictive modeling. The role is built for a self-starter, and creative, quantitative thinker; someone comfortable pushing for structured insights amidst disparate data sets, and excited about applying data and analytics to evolving Film Marketing.

At Sony Pictures, our mission is to map relevant movie and TV series content to consumers and audiences across transactional, subscription and linear viewing platforms. We're building data products and visualization tools and insights platform that will predict audience preferences and behavior for library and new releases to drive growth of engagement and consumption of Sony produced content. Sony produces franchise brands such as Spiderman, Men in Black and Jumanji, through to TV franchises such as Breaking Bad, Blacklist and Better Call Saul. Our Data team is responsible for aggregating millions of consumer data points to best in class predictive models, consumer trends systems, recommendation engines and more!

In the role of Manager, Data Analysis and Profiling for The Sony Pictures Audience Analytics and Activation Division, you must a strong analytical and technical background and believe that data profiling, quality control, data integration across disparate data sets are foundational in enabling and driving a culture where data is democratized, accessible and easily interpreted for Sony Pictures to be a consumer-centric data driven organization.

You will work in the Data Management team that is responsible for the profiling, UAT, development and management of the Sony data licenses and cloud-based data platforms and sandboxes. You will be part of a team that is instrumental in partnering with Business Intelligence Team to enable data usage across the consumer analytics team, strategic business partners and business users.

You are a data optimization expert who is driven to ensure data quality, consistency, integration, connectivity across big data sets. You will work with our data science team, our business intelligence team, our strategic analysts and our diverse users in the business. You will provide a data management service spanning from data ingestion to end-user lifecycle: Profile, ingest, connect, features engineering, model, prepare, store and disseminate data.

You are data curious and business savvy with a strong background and demonstrated ability to navigate and analyze large and diverse data sets and be able to structure data so that it is meaningful and compelling.

Core Responsibilities include:
• Work closely with consumer / audience analytics teams and technology partners as part of a complete data and analytics lifecycle.
• Conduct data lifecycle activities: problem identification, hypothesis definition, data integration, data profiling, prototyping and experimentation, data schema design, development, testing and deployment
• Conduct a broad range of analytics data management and optimization functions including development, scheduling, job optimization, version control management, data quality management, and issue resolution.
• Develop and deliver attributes and deploying data preparation processes to be utilized for data warehouses/repositories/big data platforms, self-service reporting solutions, scorecards and dashboards on user-level audience and consumer data using analytical and visualization tools.
• Work with teams to understand business requirements - translate and use complex data sources that needs to be blended, cleaned, structured and enriched into a desired output for analysis and utilized to deliver efficient and quality reports/ dashboards using various BI tools.
• Partner with analysts to optimize and improve data operational processes.
• Support User Acceptance Testing to ingest new data sets and migrate data sets to cloud platforms for data sandboxes.
• Promote and evaluate use of software development best practices (including automated unit testing, Continuous Integration, Continuous Deployment, Dev Ops).
• Execute version control, change management and continuous improvement protocols.
• Collect and refine data from disparate data sources to support business requirements.
• Partner with IT to schedule and optimize various ETL scripts. Access and create various data sources to supplement existing data.
• Troubleshoot and resolve data discrepancies, nuances and issues. Perform quality audits, identify data gaps / anomalies; conduct root cause analysis with recommended solutions, and track error resolution through completion.
• Collaborate with strategic analysts and data scientists to use expanded data sets and query techniques.
• Develop custom data-sets and execute data extract queries to support ad hoc analyses and data science initiatives.
• Create and implement data-sets for to support management, analysis, dashboard reporting and advance analytics models needs.
• Conduct ad hoc data mining and data profiling activities on new data.
• Create documentation and logs for new and existing data sources including: drafting data dictionaries, providing data field definitions, developing common business data language, data nuances, data summaries and tracking aggregate tables and features engineering calculations.
• Maintain data catalog with additions, changes and deletions to ensure most up-to-date information is available to other team members.
• Present and communicate data summaries and presentations with the goal of data education

Preferred Qualifications:

• Minimum 4+ years working as a Data Analyst, Data Profiler, Business Analyst for a medium to large scale BI implementation
• Big Data concepts and common components including open source Spark (AWS) and in memory (RAM) analysis and multiple languages
• Basic Java Script (useful if building APPS – but Python substitute to this)
• Scala (relevant to streaming data)
• Python, R
• Data products – how to productionalize Data Science (''DS'') prototypes (build logic and components with scale)
• Understanding of data engineering (data building blocks)
• Advanced SQL, and/or Python scripting experience
• Strong technology background: ETL and/or SQL coding experience: IBM Data Stage and Pentaho
• Understanding of API – working and connecting with API (Software engineering)
• Understand file constructs such Json, xml, flat files (CSV text files)
• Understanding of .Net (C#, VB Script, Java script) OR Java application development
• Experience in trouble shooting and resolving issues data systems
• Experience designing high performing database queries / indexes and troubleshooting database performance issues

Knowledge of:
• Excellent written and verbal communication skills
• Ability to deliv

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