Responsibilities

- Build, maintain, and optimize batch and real-time data pipelines.
- Develop clean, efficient, and well-tested SQL and data processing code.
- Collaborate with product, analytics, and engineering teams to deliver data solutions.
- Support data modeling and scalable datasets for downstream users.
- Monitor pipelines, troubleshoot issues, and improve reliability and performance.
- Implement data quality, testing, and observability practices.
- Contribute to technical discussions, architecture, and design decisions.
- Identify and resolve recurring issues and technical debt.
- Document data systems and share knowledge with the team.
- Take ownership of data products and pipelines.

Preferred candidate profile





- Hands-on experience with AWS data services such as Glue, Redshift, Athena, or EMR.
- Strong SQL skills and understanding of data modeling.
- Experience developing ETL/ELT pipelines for batch or real-time data.
- Familiarity with Spark, Airflow, dbt, or similar tools.
- Proficiency in Python or another data engineering language.
- Understanding of data quality, testing, monitoring, and observability.
- Basic knowledge of CI/CD and version control.
- Robust problem-solving skills and curiosity to understand business requirements.

📌 Data Engineer at A FinTech Company (Bengaluru)
🏢 Talentzo Delhi
📍 Bengaluru