Data Engineer Advisor

Job Summary

We are seeking a highly skilled ETL Developer with 6+ years of experience in designing, developing, and maintaining modern data integration and transformation solutions. The ideal candidate should have strong hands-on expertise in Snowflake, Data Build Tool (DBT), and Fivetran, along with excellent SQL development skills. The candidate should have experience building scalable data pipelines, implementing data quality controls, and supporting enterprise data warehousing and analytics initiatives.

Additionally, the candidate should be well-versed in CI/CD practices, Git-based development workflows, and deployment automation to support modern data engineering practices.

Technical Skills

• 6+ years of experience in Data Engineering with at least 2+ years in Fivetran,  Snowflake and DBT.
• Strong hands-on expertise in Snowflake Data Cloud.
• Strong hands-on experience with DBT (Data Build Tool) for data transformations and modeling.
• Experience designing and developing data pipelines across Bronze and Silver layers in modern data lakehouse architectures.
• Strong understanding of data warehousing concepts, dimensional modeling, and data transformation patterns.
• Experience with SQL performance optimization and Snowflake tuning techniques.
• Familiarity with CI/CD practices, Git-based development, and deployment automation.
• Understanding data quality, testing, monitoring, and governance frameworks.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for ingesting, transforming, and loading data from multiple source systems.
• Build and optimize data transformation pipelines using DBT following modular and reusable development practices.
• Develop and maintain data models in Snowflake, including staging, intermediate, and curated layers.
• Configure, manage, and troubleshoot data ingestion pipelines using Fivetran.
• Write complex and high-performance SQL queries, stored procedures, views, and data validation scripts.
• Implement data quality checks, reconciliation processes, and monitoring mechanisms to ensure data accuracy and reliability.
• Collaborate with Data Architects, Data Engineers, Analysts, and Business stakeholders to understand requirements and deliver data solutions.
• Optimize Snowflake performance through effective partitioning, clustering, warehouse sizing, and query tuning.
• Develop and maintain source-to-target mappings, technical specifications, and data lineage documentation.
• Troubleshoot production issues and perform root cause analysis for data-related incidents.
• Participate in code reviews and ensure adherence to development standards and best practices.
• Implement and support automated deployment processes across development, testing, and production environments.