Responsibilities
Build, maintain, and optimize batch and real-time data pipelines.
Develop clean, productive, 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.
Solid 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.
Solid problem-solving skills and curiosity to understand business requirements.

📌 Data Engineer At A Fintech Company Bengaluru
🏢 Talentzo Delhi
📍 Bengaluru