Key Responsibilities

• Design logical and physical data models.
• Build analytics-ready Tier-2 data models using dimensional modeling and star-schema principles where appropriate.
• Define facts, dimensions, relationships, measures, and transformations.
• Develop ingestion, transformation, and orchestration pipelines.
• Build and maintain batch and streaming data-processing workflows.
• Support data replication and historical data backfills.
• Implement data-quality controls and validation logic.
• Perform unit, integration, regression, and data-quality testing.
• Reconcile source and target datasets.
• Prepare production-ready code, configurations, and data models.
• Participate in code reviews and approved release processes.
• Support production deployments and post-deployment validation.
• Troubleshoot defects and perform root-cause analysis.
• Create technical documentation, release notes, and operational materials.
• Participate in daily stand-ups, design reviews, demonstrations, and knowledge-transfer activities.