Senior python data engineer – etl

6 days ago

Mount Abu, India AIMLEAP Full time

Senior Python Data Engineer – ETL & Pipeline Development Experience: 5 to 12 Years Location: Remote (WFH) / Bangalore / India Mode of Engagement: Full-time No. of Positions: 5 Educational Qualification: B. E / B. Tech / M. Tech / MCA / Computer Science / IT Industry: IT / Data / AI / Legal Tech / Enterprise Solutions Notice Period: Immediate Joiners Preferred What We Are Looking For: 5–12 years of hands-on experience building end-to-end ETL pipelines and data workflows from scratch (Python + SQL). Strong expertise in Python for data transformation, automation, and orchestration (Pandas, Airflow, custom schedulers). Ability to write complex SQL queries, optimize performance, and design scalable database schemas. Experience integrating and consuming RESTful APIs for ingestion, transformation, and delivery pipelines. Working knowledge of AWS / GCP / Azure (S3, Lambda, EC2, Big Query, etc.). Hands-on exposure to Docker, Kubernetes, and CI/CD for deploying ETL & data workloads. Experience building or working with AI-driven / automated data pipelines (preferred). Responsibilities: Design, architect, and build complete ETL pipelines for multi-system data extraction, cleaning, transformation, and loading. Develop custom Python-based data automation frameworks to improve quality and speed. Build and optimize SQL queries, tables, and database structures for analytics & AI use cases. Create and manage API-based data ingestion / integration workflows. Deploy and maintain workloads using Docker, Kubernetes, and CI/CD tools. Collaborate with product, AI, and analytics teams to deliver intelligent data solutions. Set up data validation, monitoring, logging, and alerting mechanisms for production pipelines. Continuously optimize pipelines for performance, cost, scalability, and reliability. Qualifications: Bachelor’s or Master’s degree in Computer Science / Engineering / IT. Expertise in Python (Fast API / Flask / Django), SQL, and REST API development. Strong understanding of data modeling, ETL concepts, and pipeline orchestration (Airflow / Prefect / Dagster). Experience with AWS (S3, Lambda, EC2, Glue, Athena) or GCP/Azure equivalents. Hands-on experience with Docker, Kubernetes, and Git-based CI/CD workflows. Strong debugging, problem-solving, and analytical capabilities with ownership mindset.

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