Data Engineer

Only Visa Independent Consultants - No C2C - Only W2 Warren MI - Onsite Role Data Engineer – Role Summary & Job Description (Legacy Support & Cloud Modernization – Azure + Databricks) Role Summary We are seeking a Data Engineer to support and evolve our enterprise data platform, which integrates data from multiple ERP systems into a centralized analytics environment. This role is responsible for maintaining our existing SQL Server and SSIS-based data warehouse while driving the transition to a modern Azure-based architecture leveraging Azure Data Factory, Databricks (Lakehouse), and Power BI. The position requires a balance of strong technical expertise and business acumen. The ideal candidate will not only build and maintain data pipelines, but also partner with business stakeholders to deliver high-quality, trusted data that drives decision-making, operational efficiency, and measurable business value. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Key Responsibilities Legacy Data Platform Support • Maintain and enhance SSIS packages for data extraction, transformation, and loading • Support SQL Server data warehouse (staging, ODS, reporting layers) • Troubleshoot data issues, job failures, and performance bottlenecks • Optimize SQL queries, stored procedures, and indexing strategies • Ensure reliability of scheduled jobs via SQL Server Agent \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Cloud Data Engineering (Azure + Databricks) • Design and develop data pipelines using Azure Data Factory (ADF) • Ingest and organize data into Azure Data Lake (Bronze/Silver/Gold layers) • Build scalable data transformations using Databricks (Spark SQL, PySpark) • Create curated, analytics-ready datasets for Power BI • Implement Delta Lake and support data governance (e.g., Unity Catalog) \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Migration & Modernization • Analyze and document existing SSIS/SQL pipelines • Translate legacy ETL processes into modern ELT patterns • Support phased migration strategy (coexistence of legacy and modern platforms) • Reduce technical debt and improve pipeline maintainability • Establish standards for data modeling, naming, and architecture \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Data Modeling & Business Value Creation • Design dimensional models (fact and dimension tables) aligned to business processes • Integrate and standardize data across multiple ERP systems • Translate business requirements into scalable data solutions • Partner with stakeholders to identify high-impact use cases for data and analytics • Deliver datasets that enable reporting, forecasting, and operational insights \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Data Quality & Governance • Implement data validation, reconciliation, and monitoring processes • Ensure data accuracy and consistency across systems during migration • Define and enforce data quality standards and controls • Support data lineage, documentation, and transparency initiatives \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Collaboration & Stakeholder Engagement • Work closely with business stakeholders, analysts, and BI developers • Support Power BI semantic models and reporting solutions • Communicate technical solutions in business terms • Act as a bridge between IT/data teams and business functions \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Required Qualifications • 4–8+ years of experience in data engineering or data warehousing • Strong SQL skills (T-SQL and/or Spark SQL) • Hands-on experience with SSIS and SQL Server • Experience with Azure Data Factory (ADF) or similar tools • Experience with Databricks (Spark, Delta Lake, or similar platforms) • Solid understanding of data warehousing concepts (star schema, fact/dimension modeling) • Experience integrating data from multiple source systems (ERP experience preferred) • Proven ability to translate business requirements into technical solutions \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Preferred Qualifications • Experience migrating legacy ETL systems (SSIS) to cloud-based architectures • Proficiency in Python or PySpark • Familiarity with Medallion architecture (Bronze/Silver/Gold) • Experience with Power BI data modeling and performance optimization • Knowledge of data governance tools (e.g., Unity Catalog) • Experience with Git and CI/CD pipelines • Exposure to dbt or similar frameworks \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Technical Skills • SQL Server (T-SQL), SSIS • Azure Data Factory (ADF) • Azure Data Lake Storage (ADLS) • Databricks (Spark SQL, PySpark, Delta Lake) • Data modeling (Kimball methodology preferred) • Performance tuning and query optimization • Version control (Git)