Sr. Data Engineer

Key Responsibilities • Design, build, and maintain robust data ingestion and transformation pipelines using AWS and Snowflake. • Support data management migration activities, including mapping, data quality validation, and data integration between legacy and target systems. • Collaborate with data architects, data stewards, and business stakeholders to ensure consistent data definitions and lineage. • Integrate data from diverse sources (ERP, CRM, marketing, and external systems) into unified data models. • Implement and optimize ETL/ELT processes using tools like AWS Glue, Python, and SQL. • Develop and maintain data models, metadata, and data quality frameworks to support master data initiatives. • Monitor, troubleshoot, and optimize data pipelines for performance, cost, and reliability. • Contribute to automation, DevOps, and CI/CD practices within the data engineering environment. Required Qualifications • 5+ years of professional experience in Data Engineering or related roles. • Strong experience with AWS data ecosystem (e.g., S3, Glue, Lambda, Redshift, Athena, EMR). • Proven experience working with Snowflake (data modeling, performance tuning, Snowpipe, Streams & Tasks). • Hands-on experience with data platform integrations preferred • Strong SQL and Python skills for data transformation and automation. • Familiarity with data governance, data quality, and metadata management concepts. • Experience with API integrations, REST/SOAP services, and cloud-native data architecture patterns. • Strong understanding of data modeling (conceptual, logical, and physical) and master data domains (Customer, Product, Vendor, etc.).