Senior AI Data Engineer
INR 2800K-4200K (estimate) Senior-level Full Time
Tasks
- Architect end-to-end data solutions
- Build event driven streaming ingestion
- Conduct architecture and code reviews
- Define data engineering standards and patterns
- Define data quality framework and remediation SLAs
- Design production ELT ETL pipelines
- Design reusable lakehouse components
- Design semantic models and DAX patterns
- Drive data governance and lineage workflows
- Handle late arriving data
- Implement Delta Lake and SCD transformations
- Implement automated data quality validation
- Integrate data quality gates into CI CD deployments
- Lead Power BI governance and deployment pipelines
- Lead master data management initiatives
- Lead technical discovery for new data initiatives
- Maintain technology radar and run tool evaluations
- Mentor data engineering team
- Optimize Spark pipeline performance
- Partner on feature store and embedding pipelines
- Present architecture proposals and governance roadmaps
- Structure and version gold layer datasets for AI
Perks/Benefits
Skills/Tech-stack
Access Control | Audit Logging | Avro | Azure | Azure APIM | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Data Lake Storage Gen2 | Azure DevOps | Azure Key Vault | Azure Synapse | Azure Synapse Analytics | Broadcast joins | Business glossary | CI/CD | Column-Level Security | Copilot in Fabric | Copilot in Power BI | Cost Based Query Planning | DAX | Data Factory | Data Governance | Data Lake Storage Gen2 | Data Lineage | Data Management | Data Quality | Data Retention | Data Stewardship | Data Vault | Data Vault 2.0 | Data retention policies | Databricks | Dataflows Gen2 | Delta Lake | Delta Live Tables | Delta Live) | ELT | ETL | Event Driven | Event-driven architecture | Feature Store | GDPR | GitHub Actions | Infrastructure as Code | JSON | Key Vault | LLM | Lakehouse | Liquid clustering | MDM | Master Data | Master Data Management | Medallion Architecture | Microsoft Data | Microsoft Data Factory | Microsoft Fabric | Parquet | Partitioning | Power BI | PySpark | Python | Query Optimization | Query Planning | RAG | REST APIs | RLS | Retention policies | Row Level Security | SCD Type 6 | SCD Type-2 | SQL | Semantic layer | Spark Query Optimization | Streaming Ingestion | Synapse Analytics | Terraform | Type 2) | Unity Catalog | Unity Catalog Access Control | Vector Databases | YAML | Z-ordering | “as-code”
Education
N/A
Roles
AI Data Engineer | Data Engineer | Engineer | Senior AI Data Engineer
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