Senior Data Engineer

Key Responsibilities

· Build, deploy, and manage data pipelines using Python and PySpark

· Develop and optimize ETL/ELT processes to support data integration across systems

· Work directly with GCP and AWS services to implement scalable cloud-based data solutions

· Own data workflows end-to-end — from ingestion to transformation to storage

· Continuously monitor and improve pipeline reliability, speed, and data quality

· Use GenAI and automation tools to speed up development and reduce manual effort

· Proactively debug, troubleshoot, and resolve data engineering issues

· Ensure data is available and trustworthy for analytics and downstream systems

· Deliver high-quality code and documentation with a bias for action

Required Skills & Qualifications

· Strong proficiency in Python and PySpark

· Working experience with cloud platforms like GCP and/or AWS

· Solid understanding of ETL/ELT, data warehouse and data lake concepts.

· Proficient in working with relational databases—preferably PostgreSQL and MySQL—as

well as non-relational databases, with a focus on MongoDB.

· Driven by delivery and results — you get things done efficiently

· Self-starter attitude with minimal need for hand-holding

· Excitement for automating work using GenAI or scripting tools

· Familiarity with SCD, CDC, Real-time Streaming vs Batch-processing.