Sr. Data Engineer

Location: Deerfield, IL (hybrid onsite 2 days a week) Employment Type: Contract-to-hire Overview The Senior Data Engineer supports enterprise data unification and analytics initiatives by designing, building, and optimizing scalable data infrastructure. This role is a key contributor to an enterprise-wide ERP transformation based on Microsoft Dynamics 365, enabling consistent, reliable, and timely data across business units. Working within a Data & Analytics team, the Senior Data Engineer partners closely with analytics, business, and technology stakeholders to deliver a trusted, unified data foundation that supports reporting, dashboards, and advanced analytics. What You Will Do Design, build, and maintain automated ETL/ELT data pipelines that ingest and transform data from Microsoft Dynamics 365 and legacy systems into an Azure Synapse data lake and enterprise data warehouse Monitor, optimize, and support data pipeline performance to ensure reliable, timely data refreshes and efficient resource utilization Implement data quality checks, validation rules, and cleansing processes to ensure data accuracy, consistency, and readiness for enterprise-wide analysis Support data unification efforts by integrating data from multiple business units and systems without altering source system integrity Contribute to the design and evolution of enterprise data models, including dimensional and star schemas, to support standardized reporting and unified business definitions Define and maintain master data structures and relationships that enable analysis across both ERP and non-ERP data sources Prepare curated and optimized datasets for business intelligence and analytics use cases, including Power BI dashboards and self-service reporting Write and optimize SQL queries and develop new pipeline components to support reporting, analytics, and ad hoc data needs Collaborate with business analysts, business intelligence developers, ERP specialists, and other stakeholders to translate reporting and analytics requirements into technical solutions Apply data engineering and analytics best practices, including version control, documentation, code review, and performance tuning Support data governance standards related to security, privacy, access controls, and overall platform scalability and reliability What We Are Looking For Technical Qualifications Required Experience designing, developing, and supporting data pipelines (ETL/ELT) that integrate data from multiple systems Strong SQL skills, including writing and optimizing complex queries, joins, and stored procedures in Microsoft SQL Server or comparable relational databases Hands‑on experience with Azure Synapse Analytics, Azure Data Factory, or similar cloud‑based data warehousing and integration platforms Experience working with large datasets in cloud or hybrid data environments Working knowledge of data modeling concepts, including fact and dimension tables and schema design for analytics and reporting Experience supporting business intelligence tools, particularly Microsoft Power BI, including datasets and dataflows Ability to use scripting or programming languages such as SQL, Python, or PySpark for data transformation and automation Preferred Experience integrating data from enterprise resource planning or customer relationship management systems, including Microsoft Dynamics 365 Familiarity with Azure Synapse Link for Dataverse or similar ERP data extraction and synchronization approaches Exposure to Apache Spark within Azure Synapse environments Knowledge of data quality, profiling, or validation frameworks Experience with legacy Microsoft business intelligence tools such as SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), or SQL Server Reporting Services (SSRS) Core Competencies Clear and effective communication with both technical and non-technical stakeholders Strong problem‑solving skills and attention to detail when working with complex data sets Ownership and accountability for data quality, reliability, and outcomes Collaborative mindset and ability to work effectively across cross‑functional teams Adaptability in a changing enterprise and transformation‑driven environment Ability to translate business needs into scalable technical solutions Preferred Qualifications Approximately 3–5 years of professional experience in data engineering, analytics engineering, or a related role Approximately 1–3 years of experience in data modeling or database design for analytics use cases Undergraduate degree or equivalent experience in Computer Science, Information Systems, or a related field Experience working in a multi-business‑unit or enterprise environment, including data unification or consolidation initiatives #J-18808-Ljbffr