Data Engineer (Snowflake+Azure) US Shift
Summary
Data engineer with 5+ years' experience designing and managing cloud data platforms on Snowflake and Azure, working remotely from Thiruvananthapuram on a US night shift (9:30 pm–6:30 am). Day to day involves building ELT/ETL pipelines with dbt, ADF, and Microsoft Fabric, plus BI support via Looker.
Job Description
Looking for 5+ years of Data Engineer to design, develop, and manage the data platform solution. Work Time: 9:30 pm - 6:30 am (US Shift) Mode: Remote Primary Skills • Strong experience with Snowflake as a cloud data platform; exposure to GCP is an advantage. • Hands-on expertise in dbt for data transformation and modelling. • Experience with Azure Data Factory (ADF) for data pipeline development and orchestration. • Proficiency in Looker for BI, reporting, and data visualization. • Familiarity with AI/ML platforms and proprietary AI tools is desirable. • Microsoft Fabric (Lakehouse, Warehouse, Dataflows) • Azure Data Factory (ADF) • Azure Data Lake Storage (ADLS Gen2) • Python • SQL (Advanced queries, performance tuning, data transformation) • ETL/ELT Pipeline Development • Data Modeling & Schema Design • Data Quality and Validation Frameworks • Git Version Control • CI/CD Fundamentals Responsibilities: • Actively participate in the design, implementation, and continuous improvement of end-to-end data platform architecture using modern Azure cloud technologies including Azure Data Factory, Azure Data Lake Storage, and Microsoft Fabric (Lakehouses and Warehouses). • Build scalable, reliable ELT/ETL pipelines to ingest, process, and transform data from multiple source systems including GCAS, GSS, Insurance, Savvy, and BAS systems. • Implement and maintain automated data quality checks and pipeline testing to ensure reliability and trust. • Develop and maintain data lakehouse solutions implementing medallion architecture patterns with bronze, silver, and gold layers for progressive data refinement. • Collaborate with offshore data engineering partners to deliver data engineering initiatives, providing technical guidance and ensuring quality standards. • Assist the Business Intelligence team with reporting and analytics requirements, ensuring their needs are supported through effective data solutions. • Contribute to and adhere to established data governance and security practices, including metadata management, data quality frameworks, and data cataloging, to promote trust and reliability. • Enable business functions with clean, structured data that supports compliance reporting, customer insights, fraud detection, and product development. • Provide detailed documentation, knowledge transfer, and training to internal teams to build data literacy