Sr. Data Engineer

Location:

Deerfield, IL (hybrid onsite 2 days a week)

Employment Type:

Contract-to-hire

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.

• 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

• 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

• 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)

• 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

• 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