Role Summary :

Own design, reliability and performance of data pipelines, ETL/ELT workflows, data marts, APIs, data quality checks and integration layers, so BI and AI teams receive clean, trusted, timely data.

Key Responsibilities :

- Design and maintain pipelines, ETL/ELT workflows, streaming, data lake and integration layers.

- Establish data quality checks and monitoring and drive change in the organization.

- Own production reliability and performance; drive incidents to root cause.

- Mentor and review the work of the junior Data Engineer.

- Partner with Data Scientist, AI Engineers and Business Analyst and support them with data.

- Handle real-time and batch data processing.

What We Expect From You :

- Build pipelines that are reliable and monitored, not just functional on day one.

- Drive production incidents to root cause, not just a quick patch.

- Communicate data availability and quality issues to BI and Analyst teams before they discover them downstream.

- Balance speed of delivery with long-term maintainability.

Qualifications & Skills :

- 4 - 7 years in data engineering: SQL, Python, ETL/ELT orchestration.

- Cloud data platform experience (Azure preferred): pipelines, storage, APIs.

- Strong understanding of data lake and data architecture.

- Data modelling for analytics (star schema) and data quality frameworks.