Data Engineer - AI and Data Science Engineer II
Deloitte (company site, opens in a new tab)2–4 yrsBengaluruOn-siteDirect career pageEst. 8–16 LPA
Posted 20h ago
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Job description
Structured overview of role & requirements
About This Role
- Build and maintain batch data pipelines using SQL, Python, and PySpark to ingest, transform, and serve sports industry data such as fan, ticketing, sponsorship, CRM, and commercial datasets.
- Implement data quality checks, validation, and documentation to ensure trustworthy data assets that support analytics, machine learning, and AI product features.
- Collaborate with product managers, data scientists, application engineering, and DevOps teams to deliver production-ready data assets, support pipeline deployment, monitoring, and troubleshooting, and participate in Agile processes.
Minimum Requirements
- Bachelor's degree in Computer Science, Engineering, IT, Mathematics, Statistics, or related field, or equivalent experience.
- 2-4 years of experience building and supporting data pipelines in product, platform, or data-intensive environments.
- Proficiency in SQL and Python including writing, testing, and tuning data transformation code; experience with at least one cloud data platform (Snowflake, Databricks, BigQuery, or PostgreSQL).
- Experience with Spark/PySpark or comparable distributed data processing frameworks and workflow orchestration; familiarity with Git/GitHub and Agile development; must be based in India and able to work virtually with US stakeholders.
Ideal Candidate Profile
- Early-career data engineer comfortable building scalable data pipelines and reusable ETL/ELT components under senior guidance.
- Experience or strong interest in sports-related data domains such as fan engagement, sponsorship, ticketing, and CRM data.
- Capable of collaborating across product, data science, and engineering teams to deliver production-grade, trustworthy data assets in an Agile product environment.