SDE II - Data Platform - Lucknow
Mission
Contribute to building a self-serve Data Platform-as-a-Product enabling scalable, reliable, and easy-to-use data infrastructure across batch and streaming workloads.\
Core Responsibilities
Build and maintain scalable data pipelines (batch & streaming) using Spark/Flink
Develop integrations across Airflow, Iceberg, and cloud platforms
Apply best practices in data modeling, partitioning, and query optimization
Support Kubernetes-based data platform workloads and troubleshoot issues
Optimize pipelines for performance, cost, and reliability
Implement monitoring, logging, and data quality checks
Participate in on-call and incident resolution
Required Skills
3-6 years in data/platform engineering
Strong fundamentals: SQL, data modeling, partitioning, optimization
Hands-on with Spark (PySpark/Scala); exposure to Flink is a plus
Experience with Airflow (or similar orchestration tools)
Familiarity with data lake formats (Iceberg/Delta/Hudi)
Working knowledge of Kubernetes & cloud (GCP/AWS/Azure)
Programming: Python (must-have), Scala (good-to-have)
Exposure to CI/CD, Git, and IaC (Terraform/Helm basics)
Good to Have
Kafka / streaming systems experience
DBT, Great Expectations, or similar tools
Observability tools (Prometheus, Grafana)
Metadata/catalog tools (OpenMetadata/DataHub)
Success Metrics
Delivers reliable, production-ready pipelines
Improves performance and platform usability
Strong ownership, debugging, and collaboration skills
| Location | Lucknow, CA |
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