Lead Data Engineer

Tasks

• Architect cloud data platform
• Build ETL and ELT pipelines
• Build dimensional models
• Conduct incident response and on call
• Create governed datasets for machine learning
• Design and scale streaming data pipelines
• Design data warehouse schema
• Develop BI dashboards and reporting
• Implement change data capture pipelines
• Implement monitoring and alerting
• Implement real time replication pipelines
• Integrate AI powered analytics and natural language querying
• Maintain data quality and governance
• Monitor and troubleshoot data pipelines
• Optimize OLAP workloads
• Orchestrate data workflows
• Perform root cause analysis
• Set up CI CD deployments

Perks/Benefits

• Annual company retreats
• Festival bonus
• Flexible remote days
• Health insurance
• Honeymoon package
• Hospital discounts
• Provident fund contribution
• Relocation opportunities
• Work from home

Skills/Tech-stack

AWS | AWS Step Functions | Airflow | Amazon Redshift | CDC | CI/CD | Cause analysis | Change Data Capture | CloudWatch | Data Capture | Data Governance | Data Quality | Data Warehouse | Data quality monitoring | Data replication | Datadog | Dimensional Modeling | ELT | ETL | GitHub Actions | Google Cloud | Grafana | LLM APIs | MCP | Metabase | Model Context Protocol | MySQL | OLAP | PostgreSQL | Power BI | Prompt engineering | Python | Quality monitoring | Real Time | Real-time Data | Root Cause Analysis | Root cause | Snowflake | Step Functions | Streaming | Tableau | Terraform