Contribute to architecture documentation (e.g. C4 model diagrams) and participate in design reviews
Troubleshoot data quality, pipeline failures, and performance issues, tracing errors from source to destination
Work with DevOps/security teams on service account management, credential handling, and infrastructure migrations (e.g. containerization)
Participate in on-call/support rotations as needed for production data pipelines
What You'll Bring
3+ years of experience as a Data Engineer building production-grade data pipelines
Solid hands-on experience with Apache Spark (PySpark) and SQL for data transformation at scale
Experience with cloud platforms (Azure preferred) and cloud-native data storage (e.g. Data Lake / Blob Storage)
Experience with Databricks, including familiarity with Unity Catalog or similar data governance/catalog tools
Familiarity with data governance and access control models (RBAC/ABAC), and working with sensitive, multi-tenant data
Experience integrating data pipelines with BI/visualization tools (Power BI, Tableau, or similar)
Comfortable working with API-based data ingestion tools/connectors (e.g. Adverity or similar ingestion platforms) is a plus
Solid understanding of software engineering practices: version control, CI/CD, testing, code review
Good communication skills and ability to work cross-functionally with product, engineering, and client-facing stakeholders
Nice to Have
Experience with workflow orchestration tools such as Apache Airflow
Experience with identity/access management integrations (Okta, Entra ID)
Experience with service mesh technologies (Istio) and containerized deployments (AKS/Kubernetes)
Exposure to sustainability, ESG, or carbon accounting data models
Experience with C4 model architecture documentation (PlantUML or similar
Location
DGS India - Bengaluru - Manyata N1 Block
Brand
Merkle
Time Type
Full time
Contract Type
Permanent
