- 1. Data Engineering &
- Pipeline Development

- Design and build scalable ETL/ELT pipelines using Azure Data Factory (ADF) and Fabric Data Factory.

- Implement batch, incremental, and CDC-based ingestion from diverse cloud and on‑prem data sources.

- Maintain robust orchestration with scheduling, dependency management, retries, and monitoring.

- 2. SQL Development &

- Optimization

- Develop complex SQL transformations, stored procedures, views, and analytical datasets.

- Optimize SQL workloads using indexing, partitioning, statistics management, and execution plan tuning.

- Implement data validation, reconciliation checks, and quality rules using SQL-driven logic.

- 3. DBT Transformation Engineering

- Build modular, version-controlled data models using DBT (staging, intermediate, marts).

- Implement DBT tests, documentation, macros, and incremental models for scalable ELT processing.

- Maintain lineage, quality checks, and deployment workflows using DBT Cloud or DBT Core + CI/CD.

- 4. Azure &

- Microsoft Fabric Engineering

- Develop and manage datasets and curated layers using Microsoft Fabric Lakehouse/Warehouse.

- Implement Delta/Parquet-based data structures, schema evolution, and medallion architecture patterns.

- Configure and optimize Fabric pipelines, Lakehouse tables, Warehouses, and SQL endpoints.

- 5. Performance, Quality &

- Monitoring

- Monitor performance across SQL queries, DBT jobs, ADF pipelines, and Fabric workloads.





- Implement automated data quality checks, SLA monitoring, and alerting using Azure Monitor/Log Analytics.

- Troubleshoot bottlenecks and ensure pipeline reliability through optimization and proactive maintenance.

- 6. Security, Governance &

- CI/CD

- Apply Azure and Fabric security standards: RBAC, secrets management, RLS/OLS, and workspace governance.

- Maintain Git-based version control and deploy pipelines, DBT models, and Fabric assets via Azure DevOps/GitHub Actions.

- Ensure adherence to governance standards for metadata, lineage, and KPI definitions.

- 7. Collaboration &

- Delivery

- Work with BI, analytics, and product teams to translate business requirements into scalable data solutions.

- Provide clean, well-modelled datasets for reporting, analytics, and downstream consumption.

- Document pipelines, models, dependencies, and troubleshooting guidelines for ongoing support.

- Optional: Role Scope Keywords (Good for Job Portals / ATS)

ADF, Microsoft Fabric, Fabric Data Factory, Lakehouse, Warehouse, Power BI semantic models, DAX, Power Query (M), DBT, SQL performance tuning, incremental loads, CI/CD, Azure DevOps, GitHub Actions, governance, RLS/OLS, monitoring.

Pay: ₹2,700,000.00 - ₹3,000,000.00 per year

Advantages

- Cell phone reimbursement

- Paid sick time

- Paid time off

- Provident Fund

Work Location: Hybrid remote in Bangalore City, Bengaluru, Karnataka

📌 Roles & Responsibilities — Data Engineer (SQL, DBT, Azure, ADF & Microsoft Fabric) (Bengaluru)
🏢 Drive2Thrive Consultancy
📍 Bengaluru