Data Engineer

About the Role

Own the pipelines that move client data from operational databases and third-party APIs into the warehouse behind their reporting. You will write Python and SQL transformations, schedule them, investigate failures, and work directly with analysts who depend on the tables you publish. Day-to-day work spans AWS services such as S3, Glue, and Redshift.

Key Responsibilities

• Build and schedule batch pipelines that load source systems into the warehouse daily
• Write SQL transformations producing clean, documented tables for analysts and dashboards
• Monitor pipeline runs, investigate failures, and fix root causes rather than rerunning
• Model warehouse schemas with analysts so reporting queries stay fast and understandable
• Manage storage and compute costs on AWS and flag unexpected increases early
• Add data quality checks that catch missing rows and broken joins quickly

Requirements

• Three to five years building production data pipelines with Python and SQL
• Hands-on experience with a scheduler such as Airflow, Dagster, or Step Functions
• Working knowledge of AWS data services including S3, Glue, and Redshift
• Comfortable optimising slow SQL queries and reading execution plans when performance drops
• Experience with Git-based workflows, code review, and deploying pipelines through CI
• Bachelor’s degree in computer science, statistics, engineering, or equivalent working experience

What We Offer

• Competitive salary benchmarked to market rates in Pune
• Structured progression with a defined skills framework
• Sponsored certifications and a yearly learning budget
• Hybrid working with flexible hours around core collaboration time
• Health insurance for you and your immediate family
• Peer code review and mentoring from senior engineers on every project