Sr. Data Engineer

• *About the Team**

We are a global media and technology organization building the data platforms that power entertainment, sports, streaming, and advertising products loved by hundreds of millions of users worldwide. Our Data Platforms team, part of a large Enterprise Technology organization, manages the entire data engineering lifecycle — from ingestion and transformation to data products consumed by Data Science, Analytics, and Product teams.

We are establishing Bangalore as a Strategic Engineering Hub and are looking for high\-caliber data engineers at various levels from Junior data engineer to Sr Manager to join us in building the next generation of data platform. Serve various use cases involving marketing, entertainment, product data telemetry. You will work on petabyte\-scale datasets, collaborate with US\-based counterparts, and own the design and delivery of business\-critical data pipelines, storage, processing layers.

• *What We Are Looking For**

• *Experience**
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• 5\+ years of hands\-on data engineering experience building large\-scale data pipelines in a production environment.
• Industry background: Previous experience at a top\-tier technology company, global product company, or data\-intensive organization where you have worked with large\-scale (TB to PB) datasets.
• Demonstrated track record of owning and delivering complex data engineering solutions end\-to\-end, from design to production.

• *Technical Skills — Required**
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• Python and Scala: Strong programming fundamentals in both languages; ability to write clean, efficient, production\-grade code.
• Apache Spark / PySpark: Hands\-on experience building distributed data processing jobs at scale.
• Databricks: Practical experience building, scheduling, and operating pipelines on Databricks (Delta Lake, Databricks workflows, Unity Catalog preferred).
• Cloud — AWS: Strong familiarity with core AWS services: S3, EMR, EC2, Glue, IAM; experience building and deploying cloud\-native data solutions.
• SQL \& MPP databases: Advanced SQL skills; hands\-on experience with at least one MPP or cloud data warehouse (Snowflake, Redshift, or BigQuery).
• Orchestration: Experience with Apache Airflow or equivalent workflow orchestration tools for managing complex pipeline DAGs.
• Data Modelling: Solid grasp of data modelling concepts — dimensional modelling, star/snowflake schemas, data vault, or domain\-oriented modelling.
• Micro\-services: Working knowledge on micro\-services development.