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Popular mid-level data-engineer role in Bangalore with common skills and experience, leading to high competition.
Core data engineering skills (Spark, Databricks, AWS) are highly transferable across industries.
Explicit 4-5 years plus Databricks, Spark, AWS, dbt and advanced SQL requirements create high shortlisting strictness.
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Design, develop, test, and maintain scalable big data pipelines on Databricks and AWS, supporting the company’s game analytics and BI dashboards.
Own pipeline reliability including monitoring, alerting, incident response, and cost optimization to ensure high-quality data delivery.
Collaborate cross-functionally with engineering, analytics, and product teams to translate data requirements into robust infrastructure and manage AWS data infrastructure components (IAM, S3, Glue).
4-5 years of professional data engineering experience.
Hands-on experience with Databricks platform, Apache Spark (PySpark or Spark SQL), and advanced SQL skills for complex transformations and performance tuning.
Practical experience managing AWS data services including S3, IAM, and Glue.
Ability to work onsite in Bangalore, India, 5 days per week.
Experienced in designing and operating batch and streaming big data pipelines following modern architecture patterns (medallion/lakehouse).
Comfortable managing end-to-end data infrastructure ownership including pipeline reliability, cost, and governance in a fast-paced environment.
Collaborative operator who communicates clearly with cross-disciplinary teams and aligns data engineering efforts to business decisions without ambiguity.