Data Engineer III – Databricks, PySpark, AWS (Bengaluru)
JPMorgan Chase · Bengaluru
| Company | JPMorgan Chase |
|---|---|
| Role | Data Engineer III – Databricks, PySpark, AWS (Bengaluru) |
| Location | Bengaluru |
| Work mode | On-site |
| Experience | 3–6 years |
| Job type | Full-time |
About this job
JPMorgan Chase is hiring a Data Engineer III in Bengaluru for the Commercial & Investment Bank. You will design, build and maintain batch and streaming data pipelines with PySpark and Databricks.
The role owns data modelling and solution design for data products, writes and tunes complex SQL, and fixes Spark issues such as skew and shuffle problems. AWS S3 and related services are used for storage and processing.
Eligibility
- Formal training or certification in data engineering and 3+ years of applied experience
- Expert SQL: complex joins, window functions, CTEs and tuning
- Strong production Python and deep Spark/PySpark
- Strong Databricks experience for large pipelines
- Batch and streaming experience and AWS S3 familiarity
Skills required
What you will do
- Build batch and streaming pipelines with PySpark and Databricks
- Own data models and target-state design for data products
- Build scalable ingestion and transformation for large datasets
- Tune Spark workloads for skew, shuffle and memory
- Follow good engineering practice with reviews and version control
How to apply
- Open the official JPMorgan Chase job page with the Apply button and submit your application there.
- Tailor your resume to Spark pipelines you built on Databricks, the data volumes and the tuning you did.
Before the interview, prepare:
- Spark tuning: skew handling, salting, AQE and shuffle partitions
- SQL: window functions and reconciliation queries
- Data warehousing: SCD types and partitioning strategy
- Streaming: checkpoints, late data and exactly-once writes to Delta
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