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Software Engineering Manager (Data Engineering)EDO • United States
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Software Engineering Manager (Data Engineering)

EDO
  • US
    United States
  • US
    United States
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Über

Software Engineering Manager (Data Engineering)
Build the future, spark innovation and align your career with purpose. McKinstry is innovating the waste and climate harm out of the built environment and creating lasting impact. Together, we're building a thriving planet. Buildings are a leading contributor to the climate crisis, generating nearly 40% of total global energy-related carbon emissions. We're making a lasting impact on our industry and within our communities by addressing the climate, affordability and equity crises through: renewables and energy services engineering and design construction and facility services To get where we're going, we need big thinkers, problem solvers and collaborative mindsets. Does that sound like you? The Opportunity with McKinstry McKinstry is building a modern, scalable data platform to power analytics, reporting, and AI-driven decision-making—and we're looking for a Software Engineering Manager (Data Engineering) to lead the team at the center of that transformation. In this role, you'll manage and develop a team of data engineers building and operating McKinstry's Azure Data Lakehouse. You'll guide the evolution from Azure Synapse Analytics to Microsoft Fabric, shaping the architecture and engineering practices that underpin enterprise-wide data access, governance, and insight. Your team's work will directly enable Power BI reporting, advanced analytics, and emerging AI capabilities across the organization. This is a high-impact opportunity for a strong people leader who is also deeply technical in modern data platforms. Success requires proven management experience—coaching, mentoring, and growing engineers—combined with hands-on technical leadership in data engineering, data modeling, and cloud-based data services. You'll set the technical direction for McKinstry's data platform, drive governance and quality standards, and collaborate across analytics, application, and business teams. This role is based in Seattle, WA and operates on a hybrid work schedule. What You'll Be Doing
Technical Contribution In collaboration with Business Technology leadership, lead the design, development, and operation of McKinstry's Azure Data Lakehouse, including data ingestion, transformation, storage, and serving layers. Provide insights to guide the platform migration from Azure Synapse Analytics to Microsoft Fabric, ensuring continuity, performance, and scalability throughout the transition. Oversee the development of robust ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, and Fabric Dataflows to move and transform data across the enterprise. Ensure data models follow established patterns such as medallion architecture (bronze/silver/gold) and dimensional modeling (star schema) to support analytics and reporting. Partner with Business Tech Analytics management and Power BI developers and analysts to ensure the data platform delivers reliable, performant semantic models and datasets for enterprise reporting. Ensure solutions are designed with scalability, performance, security, and reliability in mind—particularly where data enables advanced analytics and AI initiatives. Participate in Agile ceremonies, backlog grooming, sprint planning, and cross-functional coordination activities. Technical Leadership Act as a data platform subject matter expert within McKinstry's technology organization, providing technical guidance on Azure data services and architecture. Define and guide data engineering standards, patterns, and best practices across the Lakehouse platform, including data pipeline design, data quality frameworks, and testing strategies. Lead the adoption of Microsoft Purview for data governance, cataloging, lineage tracking, and compliance across the enterprise data estate. Consult with Business Technology as they drive Master Data Management (MDM) strategy and implementation, ensuring consistent, trusted data entities across systems and platforms. Evaluate and guide the use of Azure data services including Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric, and Azure Databricks where appropriate. Partner closely with leadership to inform decisions related to people, tools, processes, and the data platform roadmap. Establish and track metrics that ensure data platform stability, data quality, pipeline reliability, and business value. People Management Lead and mentor a team of data engineers focused on building and maintaining McKinstry's enterprise data platform. Provide day-to-day technical direction, coaching, and feedback to team members working across data engineering, pipeline development, and data governance. Foster a culture of continuous learning, encouraging skill development in Azure data services, Fabric, Purview, Power BI, and modern data engineering practices. Communicate a clear data platform vision and technical strategy across IT, analytics, and business stakeholders. Other duties as assigned. What You Need to Succeed at McKinstry Bachelor's degree in Information Technology, Computer Science, Data Science, or a related field, or equivalent work experience. At least 8 years of experience with increasing responsibility in information technology and data systems, including 5 years in data engineering, data platform development, or applications management. Proven experience managing and leading software or data engineering teams with a strong focus on cloud-based data platforms. Deep experience with Azure data services, including Azure Synapse Analytics, Azure Data Factory, and Azure Data Lake Storage; experience with Microsoft Fabric is strongly preferred. Strong understanding of data modeling concepts, including star schema, medallion architecture, and semantic modeling for analytics. Experience with ETL/ELT pipeline development and data transformation at enterprise scale. Familiarity with Microsoft Purview for data governance, cataloging, and lineage tracking. Experience with or exposure to Master Data Management (MDM) concepts and tooling. Working knowledge of Power BI, including how data engineering supports semantic models, datasets, and enterprise reporting. Experience with Azure Databricks, Delta Lake, or Spark-based processing is a plus. Experience working in Agile development environments. Strong organizational, prioritization, and communication skills. Ability to influence across teams and drive alignment on data standards and architecture decisions. Experience with Azure DevOps and Microsoft SQL Server preferred. Exposure to machine learning, AI-enabled systems, or advanced analytics preferred. On-call availability 24 hours, 7 days a week. Ability and willingness to travel regionally. Provide personal transportation for meetings and job visits away from the office; reimbursed. PeopleFirst Benefits When it comes to the basics, we have you covered: Competitive pay 401(k) with employer match and profit-sharing plan Paid time off and holidays Comprehensive medical, prescription, dental, and vision with low or zero deductible options and low out of pocket maximums People come first at McKinstry, and we go beyond the basic benefits with: Family formation benefits, including adoption and IVF assistance Up to 16 weeks paid parental leave Transgender inclusive benefits Commuter benefits Pet insurance "Building Good" paid community service time Learning and advancement opportunities via McKinstry University McKinstry Moves onsite gyms or reimbursement for remote workers See benefit plan documents for complete details. If you're driven by our vision to build a thriving planet together, McKinstry is the place to build your career. The pay range for this position is $110,790 - $190,700 per year; however, base pay offered may vary depending on job-related knowledge, skills, and experience. A bonus may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. Base pay information is based on market location. A bonus may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered.
  • United States

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  • English
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