Senior Manager, Data Engineering & Analytics

About the role

The Senior Manager of Data Engineering & Analytics is based at Trystar's Burnsville office. Reporting to the Head of Digital, this role is responsible for defining and executing Trystar's enterprise data strategy, designing and owning the enterprise data architecture, and building and managing modern data pipelines.

Responsibilities

• Define and execute Trystar’s enterprise data strategy aligned with business objectives, leveraging Microsoft Fabric as the core analytics and data platform.
• Design and own the enterprise data architecture, including OneLake, Lakehouse, Data Warehouse, and data integration patterns within the Fabric ecosystem.
• Establish and enforce a scalable data governance framework, including data quality standards, data cataloging, master data management, metadata management, and data lineage.
• Define data ownership, stewardship roles, and policies across the organization.
• Build and manage modern data pipelines with medallion architecture using Microsoft Fabric Pipelines, and related services.
• Oversee the development of semantic models, Power BI reports, dashboards, and self-service analytics capabilities that drive decision-making across the business.
• Ensure data solutions are performant, secure, and cost-optimized, monitoring capacity, refresh schedules, and resource consumption.
• Deliver analytics solutions that serve manufacturing, supply chain, finance, sales, and executive stakeholders with timely, trusted data.
• Recruit, develop, and lead a high-performing team of internal data professionals (engineers, analysts, architects) and manage external contractors and consultants.
• Set clear expectations, provide regular coaching, and create development plans that grow individual contributors into stronger practitioners.
• Foster a team culture grounded in accountability, collaboration, and continuous improvement, reflecting Trystar’s Play For Each Other value.
• Lead change management efforts to shift mindsets, behaviors, and processes toward enterprise data maturity.
• Build strong partnerships with leaders across operations, engineering, finance, sales, and supply chain to understand their data needs and deliver solutions that create measurable value.
• Communicate complex data concepts in clear, business-friendly language to stakeholders at all levels, including executive leadership.
• Serve as a trusted advisor to the Senior Leadership on data strategy, emerging technologies, and platform investments.

Qualifications

• Bachelor’s degree in computer science, Information Systems, Data Science, Engineering, or a related field.
• 8+ years of progressive experience in enterprise data management, spanning data governance, data architecture, data engineering, and data analytics.
• 3+ years of people leadership experience, including managing both FTEs and contractors/consultants.
• Deep, hands-on expertise in implementing medallion architecture with Microsoft Fabric, Databricks or Similar platform— including OneLake, Lakehouse, Data Warehouse, Data Factory, Synapse Data Engineering, and Power BI.
• Strong command of data modeling (dimensional, entity-relationship, semantic), ETL/ELT design patterns, and data quality frameworks.
• Proficient in writing SQL, Pyspark, and DAX.
• Demonstrated ability to build and scale data teams and capabilities in a fast-paced, growth-oriented environment.
• Proven track record of leading organizational change management related to data and analytics adoption.
• Excellent communication skills with the ability to influence senior leaders and translate technical concepts into business outcomes.

Preferred Skills

• Master’s degree in a related field.
• Experience in a manufacturing, industrial, or supply chain environment.
• Experience with ERP, CRM & other SAAS systems.
• Microsoft certifications in Fabric Analytics Engineer (DP-600), Azure Data Engineer (DP-203), or Power BI Data Analyst (PL-300).
• Familiarity with ERP data environments (e.g., Epicor, SAP, or similar).
• Experience with real-time analytics, streaming data, and IoT data integration.
• Experience operating in a private equity-backed or high-growth company where speed and accountability are paramount.
• Working knowledge of Agile or Scrum delivery methodologies in a data context.