Data Engineer / QA (SS22)

Vaco by Highspring is currently seeking a Data Engineer / QA for a 16M+ Contract opportunity that is remote. The role focuses on supporting a large-scale enterprise data modernization initiative, building cloud-native data pipelines, and ensuring data quality and governance throughout the delivery lifecycle.

Responsibilities:

• Developing Enterprise Data Pipelines / ELT Workflows / Cloud-Native Data Processing Solutions within Snowflake
• Designing / Developing Data Ingestion Pipelines Supporting Batch / Incremental / Near Real-Time Data Processing
• Developing Complex SQL Logic / Query Optimization / Transformation Processes Supporting Enterprise Analytics
• Building Python-Based Data Processing / Automation / Validation / Pipeline Support
• Developing / Maintaining DBT Models Supporting Modular Data Transformations / Testing / Documentation / Analytics Engineering Best Practices
• Modernizing Legacy ETL Workloads into Cloud-Native ELT Architectures Leveraging Snowflake / DBT
• Developing CDC Pipelines Supporting Incremental Data Loads / Synchronization / Low-Latency Data Movement
• Performing Source-to-Target Data Validation / Reconciliation / Completeness Verification to Ensure Accurate / Trusted / Consistent Data
• Supporting Data Quality Validation / QA Reviews / Testing Activities Throughout Development / Migration / Production Deployment
• Supporting Enterprise Data Migration Initiatives (Legacy Platform Modernization / Data Conversion / Validation Activities)
• Building Automated Deployment Pipelines Supporting Data Engineering Releases / Testing / Production Promotion
• Partnering with Data Engineering / Architecture / QA Teams Using Azure DevOps / Git throughout Agile Delivery

Requirements:

• Snowflake - Developing Enterprise Data Pipelines / ELT Processes / Cloud Data Warehouse Solutions within Snowflake
• SQL - Strong Experience Developing Complex SQL Queries / Stored Procedures / Data Transformations / Performance Optimization
• Python - Developing Python-Based Data Engineering Solutions Supporting Automation / Pipeline Development / Data Validation
• DBT - Experience Building Modular DBT Models / Transformations / Tests / Documentation Supporting Analytics Engineering Best Practices
• ETL / ELT Development - Experience Designing / Developing / Modernizing Enterprise Data Integration Solutions
• Change Data Capture (CDC) - Experience Implementing CDC Pipelines Supporting Incremental Data Processing / Data Synchronization
• Data Validation / Reconciliation - Experience Performing Source-to-Target Validation / Data Reconciliation / Quality Verification Across Enterprise Data Pipelines
• Data Quality / QA - Experience Supporting Data Quality Validation / Testing / QA Processes Throughout Enterprise Data Delivery
• CI/CD - Experience Building Automated Deployment Pipelines Supporting Data Engineering Development and Production Releases
• Azure DevOps - Experience Managing Agile Delivery / Source Control / Build Pipelines / Release Management within Azure DevOps
• Git - Experience Utilizing Git for Source Control / Branching / Code Reviews / Collaborative Development
• Analytical Problem Solving - Investigating Data Quality Issues / Pipeline Failures / Transformation Errors / Root Cause Analysis Supporting Continuous Improvement
• Data Vault - Designing / Supporting Data Vault Architectures for Scalable Enterprise Data Warehouse Solutions
• Kimball Methodology - Designing Dimensional Models (Star Schemas / Fact Tables / Conformed Dimensions) Supporting Enterprise Reporting / Business Intelligence
• Enterprise Data Governance - Supporting Enterprise Data Governance / Metadata Management / Business Glossary Initiatives
• Business Intelligence Platforms - Experience Supporting Modern BI / Reporting Platforms Including Power BI / Tableau / Looker
• Agile Data Delivery -Working in Agile Data Engineering / Analytics Delivery Teams Supporting Iterative Solution Development / Delivery