Senior Data Engineer

Senior Data Engineer – Enterprise Data Hub (AWS + Snowflake + DBT + PySpark + CI/CD) Job Description: We are looking for an experienced Senior Data Engineer (10+ years of data engineering experience) to join the EDH team. This role will serve as a technical resource responsible for designing, developing, supporting, and enhancing modern data pipelines built using AWS, Snowflake, and DBT. The ideal candidate should have strong hands-on experience building enterprise-scale data platforms, working with AWS, Snowflake cloud-based data engineering solutions, and supporting complex data integration and transformation processes. The candidate should be comfortable working independently, collaborating with offshore teams, and providing technical guidance. Key Responsibilities: • Design, develop, and support enterprise data pipelines using AWS, Snowflake, and DBT. • Develop and enhance metadata-driven data ingestion and transformation frameworks. • Work with AWS services to build scalable data ingestion solutions. • Implement enterprise-scale solutions using Snowflake, including database design, data loading, data transformation, security, performance optimization, and operational support. • Build dimensional models, star schema, snowflake schema, fact and dimension tables, and data structures optimized for analytics and reporting. • Develop DBT models, macros, tests, and deployment configurations. • Troubleshoot and debug data pipeline issues across AWS, Snowflake, dbt, and PySpark, perform root cause analysis, and implement solutions. • Support EDH production deployments, monitoring, and issue resolution. • Collaborate with offshore engineering teams and provide technical guidance and code reviews. • Participate in architecture discussions and recommend improvements to platform design. • Work with DevOps teams on CI/CD processes, Git-based development, deployment automation, and release management. • Implement data quality checks, validation frameworks, logging, and operational monitoring. Required Technical Skills: AWS: Strong hands-on data engineering experience with AWS data services Snowflake: Strong hands-on experience with Snowflake architecture, development, Designing data warehouse solutions using Snowflake. DBT: Strong hands-on experience with DBT development PySpark: Experience developing PySpark applications for data ingestion and cleansing. DevOps-CI/CD: Experience with deployment automation, release management, and environment promotion processes. Data Modeling: Experience designing dimensional data models (Facts, Dimensions). transformation, and optimization in cloud-based data platforms. SQL: Strong SQL skills including complex queries, performance tuning, and optimization.