About the Role

We're looking for a hands-on Data Engineer who is comfortable writing production-grade SQL, designing scalable ADF pipelines, and most importantly — questioning the data itself, not just moving it. You'll work across the data platform, from ingestion through reporting, turning undocumented source data into consistent, reliable, and well-governed assets. This is not a role for someone who wants to just build pipelines and move on; we're looking for someone who takes ownership of data quality and integrity end-to-end.

Key Responsibilities
Design, build, and optimize scalable, fault-tolerant data pipelines for ingestion and processing.
Write and maintain complex SQL stored procedures, views, and functions following engineering standards.
Analyze data patterns to identify inconsistencies and anomalies, and perform rigorous data validation.
Build and enforce data quality, validation frameworks, and automated testing to ensure data integrity.
Document data models, pipelines, and data dictionaries for both technical and business stakeholders.




Proactively seek clarification on ambiguous requirements and exercise independent judgment on technical design.
Contribute to and enforce engineering standards (SQL, ADF, Python, Git branching conventions).
Conduct peer code reviews using Git-based workflows.

Must-Have Skills
7–14 years of experience in Data Engineering.
Robust hands-on experience with Azure Databricks, Azure SQL Server, and Azure Data Factory (ADF).
Strong SQL skills (T-SQL is a plus).
Python with PySpark, DataFrames, and API integrations.
Proven experience building and optimizing production-grade ETL/data pipelines.
Robust analytical and problem-solving skills — ability to critically evaluate data, not just process it.
Robust documentation and communication skills.
Reliable job history with good communication skills.

Good to Have
CI/CD & DevOps release pipelines.
YAML configurations.
AI/MCP tooling with LLM work

📌 Senior Data Engineer Bengaluru
🏢 ThoughtFocus
📍 Bengaluru