Role-Senior Data Engineer
Experience - 7 to 15 years
Location- Pune, Hyderabad, Bangalore

Required Skills & Experience
Must Have
7-12 years of data engineering experience, with strong recent hands-on responsibility for distributed batch or streaming pipelines.
Strong hands-on Apache Spark experience using PySpark, Scala, or Spark SQL, including tuning and production troubleshooting.
Experience building lakehouse pipelines on Google Cloud Storage using Apache Iceberg or a comparable open table format.
Strong SQL skills with practical experience in profiling, transformations, joins, aggregations, incremental processing, and reconciliation.
Experience with Apache Kafka and Apache Flink or Spark Structured Streaming.
Hands-on Apache Airflow experience covering scheduling, dependencies, retries, backfills, and monitoring.
Experience with database, file, API, event, and CDC ingestion using Kafka Connect, Debezium, Datastream, or comparable tools.
Understanding of data modeling, schema evolution, data contracts, partitioning,



file formats, data quality, lineage, and governance.
Working knowledge of Git, automated testing, CI/CD, containers, GKE-based execution, Cloud Storage, Workload Identity Federation, and Secret Manager.
Solid problem solving, documentation, collaboration, and stakeholder communication skills.
Good to Have
Experience with Polaris, Nessie, REST catalogs, Trino, OpenMetadata, schema registries, Dataproc, or data-quality frameworks.
Experience with GCP data services and regulated enterprise environments.
Exposure to banking data, high-volume transaction processing, reconciliation, auditability, or data privacy controls.
Experience with reusable data-product patterns, data contracts, semantic models, or domain-oriented data platforms.
Exposure to performance engineering, recovery testing, and multi-tenant GCP data platforms.

📌 Senior Data Engineer (Bengaluru)
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