Data Engineer at A FinTech Company

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.
• Strong problem-solving skills and curiosity to understand business requirements.