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
Solid 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 (positive-to-have)
Exposure to CI/CD, Git, and IaC (Terraform/Helm basics)

Valuable 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

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sde 2 Lucknow
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📍 Lucknow