Data Engineer
Summary
Senior Data Engineer (6+ years) based in Bangalore who designs, builds, and optimizes ETL/ELT data pipelines, Snowflake data models, and SQL/Python transformations using PySpark, dbt, and Git for CodeVyasa, a product engineering services firm serving clients like Walmart, RazorPay, and Swiggy.
Role Overview
We are looking for an experienced Data Engineer with 6+ years of hands-on experience , Location -Bangalore
About Us
CodeVyasa is a mid-sized product engineering company that works with top-tier product and solutions organizations such as McKinsey, Walmart, RazorPay, Swiggy, and others. We are a team of 850+ engineers, driving innovation across Product & Data Engineering, focusing on Agentic AI, RPA, Full Stack, and GenAI-based solutions.
Must-Have Skills
- Snowflake – Strong hands-on experience with data warehousing and performance optimization
- SQL – Advanced SQL, complex queries, joins, CTEs, window functions, query optimization
- Python – Strong programming and data engineering experience
- PySpark – Hands-on experience in large-scale data processing
- dbt – Development of data transformation pipelines and models
- ETL/ELT – Strong experience designing and developing reliable data pipelines
- Data Modeling – Experience with dimensional modeling, fact/dimension tables, and schema design
- Git – Version control, branching, pull requests, and collaborative development
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Develop data transformation workflows using Python, PySpark, and dbt.
- Build and optimize data models in Snowflake.
- Write complex and optimized SQL queries for data processing and analytics.
- Implement data quality, validation, and reconciliation processes.
- Optimize Snowflake queries, workloads, and data storage for performance and cost.
- Work with business and analytics teams to understand data requirements.
- Maintain code using Git and follow standard development practices.
- Troubleshoot pipeline failures and resolve data quality/performance issues.
- Contribute to data architecture, modeling, and engineering best practices.
Why Join Us?
- Work on innovative, high-impact projects with leading global clients.
- Exposure to large-scale Data Science, AI, and Analytics initiatives.
- Continuous learning and upskilling opportunities through internal and external programs.
- Supportive and collaborative work culture with flexible policies.
- Competitive salary and comprehensive benefits package.
- Free healthcare coverage for employees and dependents.