Key Responsibilities
* Design, build, and maintain scalable data pipelines for batch and real-time data.
* Integrate data from oneD applications, websites, Smart TVs, content platforms, advertising systems, subscription systems, and third-party tools.
* Develop and maintain data warehouses, data lakes, and analytical datasets.
* Ensure the accuracy, completeness, consistency, and freshness of data.
* Build automated data-quality checks, monitoring, alerts, and reconciliation processes.
* Create reliable datasets for product, content, marketing, finance, and management reporting.
* Support analytics for user acquisition, engagement, retention, churn, subscriptions, advertising, and content performance.
* Establish consistent definitions for key metrics such as MAU, watch time, active subscribers, conversion, churn, and content completion.
* Work with Product, Engineering, Analytics, Finance, Marketing, and Content teams to understand data requirements.
* Improve tracking implementation across mobile, web, tablet, and Smart TV platforms.
* Optimize data-processing performance, storage costs, and pipeline reliability.
* Maintain clear documentation covering data sources, pipelines, schemas, ownership, and business definitions.
* Apply appropriate data security, access-control, privacy, and governance standards.
* Investigate and resolve data discrepancies and pipeline failures.
Qualifications
* Bachelor’s degree in Computer Science, Engineering, Data Science, Information Technology, or a related field.
* At least 3–5 years of experience in data engineering or a related technical role.
* Strong proficiency in SQL and Python.
* Experience building ETL/ELT pipelines and data-integration workflows.
* Experience with cloud data platforms, preferably AWS.
* Good understanding of data warehouses, data lakes, dimensional modelling, and database design.
* Experience using workflow-orchestration and data-transformation tools.
* Familiarity with APIs, event tracking, streaming data, and third-party data integrations.
* Understanding of data-quality monitoring, testing, and incident resolution.
* Ability to translate business requirements into scalable technical solutions.
* Strong analytical, communication, documentation, and problem-solving skills.
* Comfortable working with internal teams and external technology partners.







