Data Engineering Manager

Primary

Location:

Grand Rapids Employee Status:
Full-Time Workplace Type:
Hybrid

Who we are:

At LMCU, you'll find more than just a job - discover a fulfilling career where your contributions truly matter. Join our talented team at Lake Michigan Credit Union and discover the difference an employer who puts people first can make in your career and life.

About this position:
The Manager, Data Engineering leads the Data Engineering function responsible for designing, building, maintaining, and optimizing enterprise data models, pipelines, and integrations that support business needs and enable self-service analytics across LMCU. This role manages Senior Data Engineer resources, establishes data engineering standards, oversees delivery and operational support, and ensures data solutions are scalable, reliable, secure, and aligned to business priorities.

• Lead, coach, and develop Senior Data Engineers, including managing workload priorities, sprint commitments, performance feedback, career development, hiring, and day-to-day delivery expectations.
• Establish and maintain enterprise standards for data modeling, ETL/ELT development, orchestration, integration patterns, Microsoft Fabric/One Lake architecture, and reusable data products.
• Oversee the design, development, testing, deployment, maintenance, and optimization of data pipelines, curated data models, integrations, and data migrations across core banking, digital, operational, and analytics platforms.
• Ensure data pipelines and models are reliable, secure, performant, well-documented, and supportable through effective monitoring, data quality controls, lineage, and issue-resolution processes.
• Partner with Business Intelligence, Data Governance, Application Development, Infrastructure, vendors, and business stakeholders to translate business needs into scalable technical solutions.
• Enable trusted self-service analytics by delivering reliable, accessible, and well-governed data products that support reporting, analytics, and informed decision-making.
• Adhere to and champion our core values of curious minds, collaborative hearts, and continuous excellence.

• 8+ years of progressive experience in data engineering, analytics engineering, data architecture, data warehousing, or data platform development, including experience leading technical resources, delivery work streams, or project teams.
• Bachelor’s degree in computer science, information systems, information technology, data management, data analytics, engineering, or a related field; significant relevant experience may be considered in lieu of a degree.
• Hands‑on experience with Microsoft Fabric, One Lake, Data Factory, notebooks, lakehouse and warehouse workloads, SQL Server, and modern cloud data platforms.
• Strong knowledge of ETL/ELT design and orchestration, dimensional modeling, star and snowflake schemas, Kimball/Inmon concepts, and medallion architecture.
• Proficiency with SQL and Python, including data pipeline testing, observability, monitoring, and troubleshooting.
• Experience with Azure Dev Ops/Git, CI/CD practices, and modern development and deployment processes.
• Knowledge of data quality controls, metadata management, data lineage, governance, and documentation best practices.
• Experience integrating core banking, digital banking, and other operational data sources into enterprise data platforms.
• Experience working within Agile delivery environments, including Service Now or Jira intake, prioritization, and stakeholder communication.
• Relevant certifications in Microsoft Fabric, Azure, cloud data platforms, data engineering, Agile/Scrum, leadership, or project management are preferred.
• experience.
• Ability to work effectively within established priorities, standards, and…