We are seeking a detail-oriented, data operations analyst who will focus on improving the quality and reliability of our data as part of the Data Governance and Instrumentation team. Collaborating heavily with our data and product engineering teams, this role relies on previous hands-on experience with data modeling, testing and optimizing new data sources, data lineage, and other processes to address data quality.
This role directly contributes to the success of our data strategy by enabling internal clients to access, explore and monitor data, as well as perform analysis and share insights.
At Disney Streaming Services, data is central to measuring all aspects of the business, and critical to our operations and growth.
- Help improve the quality and reliability of the data we surface in our business intelligence, marketing, and other internal systems
- Develop a deep understanding of the different data sources we support and their respective pipelines
- Build queries, tools, and processes that identify potential data quality issues
- Partner with colleagues facilitating the design, build and automation of reports / dashboards that provide insight into business and product performance
- Drive processes supporting engineering and product teams to reconcile data quality issues and develop and execute on mitigation plans
- Work closely with data engineering to understand the pipelines by which data is collected, stored, and transformed for fast, easy consumption
- Identify ways to more efficiently detect and correct potential data quality concerns
- Work within the data governance team to document data processes and pipelines
- Assist in scoping and implementing data solutions, including both third-party governance tools and BI solutions
- 2+ years of analytical experience working in a fast-paced environment.
- 2+ years of work experience using SQL and Python/R or other statistical programming language.
- Familiarity with data exploration and data visualization tools like Tableau, Looker, Sisense, etc.
- Experience with complex ETL processes, data warehousing, (e.g. Redshift, Snowflake) and data governance tools
- Understanding of statistics concepts (e.g., hypothesis testing, regression analysis).
- Ability to think strategically, analyze and interpret market and consumer information.
- Strong communication and presentation skills – written, visual, and verbal presentations
- Degree in an analytical field.