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- Led and managed the Content Data organization, overseeing 5 Data Engineering teams responsible for data operations across streaming, linear, and digital platforms for The Walt Disney Company.- Directed strategic data initiatives to optimize data pipeline efficiency and cost, and enhancing content engagement reporting across multiple channels.- Shaped and prioritized product roadmaps to align with key business objectives, focusing on high-impact data solutions while managing technical debt.- Collaborated closely with Analytics, Data Science, and Business stakeholders to ensure data solutions met both operational and strategic needs.

- Led data operations for all Disney streaming services, including Hulu, Disney+, ESPN+, Star+, and Hotstar.- Partnered with Business Stakeholders, Analytics, Data Science teams, and Product Managers to leverage data for strategic decision-making, operational efficiencies, and improve user engagement.- Directed initiatives to unify data across streaming services and improve content engagement reporting across platforms.

- Led the Content Data Engineering teams for Disney Streaming Services, overseeing data pipelines for Disney+, ESPN+, and Hulu.- Championed Data Governance across the organization, partnering with the Data Governance team to establish new standards and practices.- Built strong relationships with new stakeholders to support strategic initiatives and incorporate them into the roadmap.- Transitioned to a new tech stack (AWS, Airflow, Snowflake) and developed an integration plan to unify data across streaming services.

- Built the Hulu Content and engagement Data Engineering team from the ground up, growing the team from 1 to 12 data engineers.- Designed, modeled, and deployed data solutions using Big Data technologies (Hadoop, Hive, Python, Spark, Snowflake) to power content analytics across the organization.- Implemented coding standards and best practices in aspects such as Data Quality and Data Governance, improving productivity and strengthening the Software Development Life Cycle (SDLC) for data products.- Stakeholder management, intake of requirements and assist in the definition of our Data Products and their 1-year roadmap.

- Led the design and development of data/BI projects focused on consolidating content performance data in the data lake (Hadoop).- Developed ETL pipelines (Hadoop, Hive, Spark, Presto, Google Big Query) and built a data mart for "Post Launch" reporting for content, balancing performance with data aggregation requirements.- Defined technical requirements and data architecture for Hulu’s data infrastructure, facilitating data-driven decision-making across the company.

- Developed and optimized ETL processes and data models to centralize Hulu’s data in a Data Warehouse, ensuring scalability and high performance.- Designed and implemented reports to support large datasets, optimizing performance and maintaining accuracy for high-impact analytics and reporting.- Translated features into data models and integrated them into the data warehouse to support analytics and reporting needs.- Design and Develop ETL Processes to consolidate data in centralized Data Warehouse. SQL Server | SSIS | Hive | Pig | Spark

• Lead the creation of a Data Warehouse solution using Postgres (SQL/PLPGSQL) with a team of 3 Database Developers and 1 QA Engineer.• Modeled the database structures (Normalized/Dimensional) as well as the design and development of the corresponding ETL Processes (PDI) for the first data warehouse of the company• Continuous Performance monitoring/optimization (Indexes, Query Tuning, etc.)

Writing SQL functions and scripts (PL/SQL) in Postgres databasesOptimization of existing SQL , PL/SQL codeData cleansing and uploading data to databaseDesigning and implementing new database structures for features, as well as schema optimizationResearching new database technologies / functionalities that can be implemented.Agile Methodology