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Data Platform Manager Jobs in Seattle, WA (NOW HIRING)

Manager, Data Engineering

Seattle, WA · On-site

$160K - $190K/yr

The person will mainly focus on building modern data platforms using Microsoft cloud technologies ... Collaborating with project management to plan work for delivery teams and verifying quality ...

Manager, Data Engineering

Seattle, WA · On-site

$150 - $200/hr

The person will mainly focus on building modern data platforms using Microsoft cloud technologies ... Collaborating with project management to plan work for delivery teams and verifying quality ...

Manager, Data Engineering

Seattle, WA · On-site

$160K - $190K/yr

The person will mainly focus on building modern data platforms using Microsoft cloud technologies ... Collaborating with project management to plan work for delivery teams and verifying quality ...

The person will mainly focus on building modern data platforms using Microsoft cloud technologies ... Collaborating with project management to plan work for delivery teams and verifying quality ...

Data Engineer

Kent, WA · On-site

$129K - $155K/yr

... management of Crescent's data pipelines, enabling reliable analytics and downstream business processes across all entities (Crescent, STWY, WMCK, LOWE). You will build and maintain the platform ...

Data Analyst

Redmond, WA · On-site

$162K - $172K/yr

We make and manage software platforms and products that power growth and deliver captivating experiences to consumers and employees. Our engineering, cloud, data, experience design, and talent ...

Showing results 41-60

Data Platform Manager information

See Seattle, WA salary details

$35.3K

$110.6K

$195.8K

How much do data platform manager jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data platform manager in Seattle, WA is $110,616.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,200.00 and $142,900.00 per year, depending on experience, location, and employer.

What is a data platform manager?

A Data Platform Manager is a professional responsible for overseeing the development, maintenance, and operation of an organization's data infrastructure. They manage data storage, processing, and integration solutions to ensure data is accessible, secure, and reliable for business needs. Their role often involves collaborating with data engineers, analysts, and IT teams to implement best practices and support data-driven decision-making. Additionally, they may oversee cloud data platforms, manage data governance, and ensure compliance with data privacy regulations.

What are the key skills and qualifications needed to thrive as a data platform manager?

To thrive as a Data Platform Manager, you need expertise in data architecture, database management, and analytics, typically supported by a degree in computer science or a related field. Familiarity with data warehousing tools, cloud platforms (such as AWS, Azure, or Google Cloud), and certifications like AWS Certified Data Analytics are commonly required. Strong leadership, problem-solving skills, and effective communication enable you to manage teams and coordinate with stakeholders. These skills ensure robust, scalable data infrastructures that support business intelligence and strategic decision-making.

What are some common challenges faced by data platform managers when aligning data strategy with evolving business needs?

Data Platform Managers often face the challenge of ensuring that the data infrastructure can adapt quickly to shifting business priorities and emerging technologies. Balancing the needs of various stakeholders—such as data analysts, engineers, and business leaders—while maintaining data quality, security, and scalability requires strong communication and project management skills. Additionally, keeping the platform up-to-date with new tools and compliance requirements, while managing resource constraints, is a recurring aspect of the role. Successfully navigating these challenges helps the business leverage data as a strategic asset.

What is the difference between Data Platform Manager vs Data Engineer?

AspectData Platform ManagerData Engineer
Primary FocusOversees data platform strategy, architecture, and team managementBuilds, develops, and maintains data pipelines and infrastructure
Required SkillsData architecture, leadership, project managementProgramming, ETL development, database management
CertificationsCloud certifications (AWS, Azure), data management certificationsSQL, cloud platform certifications, programming certifications
Work EnvironmentCollaborates with data teams, IT, and business unitsHands-on technical work in data engineering teams

The Data Platform Manager focuses on overseeing the data platform's overall strategy and managing teams, while the Data Engineer is responsible for the technical development and maintenance of data pipelines. Both roles require technical skills and certifications, but the manager role emphasizes leadership and strategic planning, whereas the engineer role emphasizes technical execution.

What are popular job titles related to Data Platform Manager jobs in Seattle, WA?

For Data Platform Manager jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Data Platform Manager jobs in Seattle, WA look for?

The top searched job categories for Data Platform Manager jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Data Platform Manager jobs?

Cities near Seattle, WA with the most Data Platform Manager job openings:

Infographic showing various Data Platform Manager job openings in Seattle, WA as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $110,616 per year, or $53.2 per hour.

Software Engineering Manager (Data Engineering)

McKinstry

Seattle, WA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 13 days ago


Key responsibilities

  • Lead the design, development, and operation of McKinstry's Azure Data Lakehouse, including data ingestion, transformation, storage, and serving layers.

  • Guide the migration of the data platform from Azure Synapse Analytics to Microsoft Fabric, ensuring performance and scalability.

  • Manage and mentor a team of data engineers, providing technical direction and fostering continuous learning.


McKinstry rating

9.7

Company rating: 9.7 out of 10

Based on 19 frontline employees who took The Breakroom Quiz


Job description

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. 

The McKinstry group of companies are equal opportunity employers. We are committed to providing equal employment opportunities to all employees and qualified applicants without regard to sex, gender identity, sexual orientation, age, race, color, creed, marital status, national origin, disability, veteran status, genetic information or any other basis protected by law. This policy applies to all terms and conditions of employment including, but not limited to employment, advancement, assignment, and training. This commitment to Equal Employment Opportunity is made equally as a social responsibility and as an economic and business necessity. 

McKinstry is a drug-free workplace. Employment iscontingent upon successfully passing a pre-employment drug and alcohol test, complying with the requirements of the Immigration Reform and Control Act and a Confidentiality Agreement, in addition to successful outcomes of background and reference checks. 

Applicants for this role will only be considered if they possess current US Work Authorization, and do not require employer-sponsored VISA support to begin or remain in this role. 

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