Lead, Data Engineer

Tasks

• Architect enterprise data platforms
• Build batch and real time pipelines for analytics and machine learning
• Build data products and enterprise data assets
• Collaborate with data science for model pipelines
• Coordinate backup recovery and disaster resilience
• Define data engineering platform roadmap
• Develop ETL and ELT workflows
• Enforce SLA compliance
• Ensure data quality controls
• Implement CI/CD for data workflows
• Implement data models and semantic layers
• Lead data engineering standards and best practices
• Lead data pipeline design build and deployment
• Maintain metadata management and data lineage
• Manage data platform operations and reliability
• Monitor troubleshoot and optimize data pipelines
• Oversee data governance, privacy, and security

Perks/Benefits

• N/A

Skills/Tech-stack

API Integration | Apache Spark | Azure Data | Azure Data Factory | Azure Synapse | Azure Synapse Analytics | CI/CD | Data Factory | Data Governance | Data Lake | Data Lineage | Data Modeling | Data Quality | Data Security | Data Validation | Data Warehouse | Databricks | Disaster Recovery | ELT | ETL | Lakehouse | Metadata Management | NoSQL | Python | Relational databases | Release Management | SLA management | SQL | Streaming | Synapse Analytics | Version control