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

Kanak Elite Services Inc

Sr ML Platform Manager

Seattle, WA · On-site

$144K - $190K/yr

Collaborate with cross-functional teams, including product management, data analytics, and IT, to align machine learning initiatives with business goals. Stay informed about industry trends and ...

Helion

Senior Software Engineer, Data Platform

Everett, WA · On-site

$135K - $178K/yr

They are seeking a Senior Software Engineer for their Data Platform to design, develop, and operate ... managing metadata like schemas, lineage, and access control • Collaborate with other software ...

Helion

Senior Software Engineer, Data Platform

Everett, WA · On-site

$135K - $178K/yr

The Senior Software Engineer, Data Platform will design, develop, and operate a secure, scalable ... managing metadata like schemas, lineage, and access control • Collaborate with other software ...

Deloitte

Adobe Experience Platform

Seattle, WA · On-site

... management, data usage labels and policies, access controls, deletion workflows, hygiene workflows, and audit controls * 5+ years in customer data, marketing technology, or data engineering with ...

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All JobsData Platform JobsData Platform Manager JobsData Platform Manager Jobs in Seattle, WA

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:

Data Platform Manager jobs near you
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.

Sr ML Platform Manager

Kanak Elite Services Inc

Seattle, WA • On-site

$144K - $190K/yr

Contractor

Re-posted 9 days ago

Job description

Role: Sr ML Platform Manager
 

Location: Seattle, Washington


LOCALS ONLY , NO RELOCATION CANDIDATE WILL WORK 

Architecture and Infrastructure:

Oversee the architecture of machine learning systems, ensuring scalability, reliability, and performance.

Work with cloud providers (AWS, Azure, Google Cloud) and on-premise solutions to optimize resource utilization and cost-effectiveness.

Model Management:

Develop and manage workflows for model training, validation, deployment, and monitoring.

Implement MLOps practices to streamline the lifecycle of machine learning models.

Collaboration:

Collaborate with cross-functional teams, including product management, data analytics, and IT, to align machine learning initiatives with business goals.

Stay informed about industry trends and emerging technologies to leverage new advancements in the field.

Stakeholder Engagement:

Communicate effectively with stakeholders to understand their needs and translate them into technical requirements and solutions.

Prepare and present reports or dashboards on the performance of machine learning initiatives.

Compliance and Ethics:

Ensure that machine learning practices align with ethical guidelines, data privacy regulations, and organizational policies.

Skills & Educational & Qualification Background: A degree in computer science, data science, engineering, or a related field; advanced degrees (Master's or PhD) are often preferred.

Technical Skills: Proficiency in programming languages such as Python, R, or Java; experience with machine learning frameworks (TensorFlow, PyTorch, etc.); strong understanding of data engineering principles.

MLOps Knowledge: Familiarity with tools and practices for model deployment and monitoring, such as Kubernetes, Jenkins, MLflow, and Docker.

Leadership: Proven experience in leading teams and managing projects, excellent communication skills, and the ability to mentor and develop team members.

Problem Solving: Strong analytical and problem-solving skills, with the ability to tackle complex technical challenges.

Thanks & Regards,

YOGITA

✉️ Yogita@kanakits.com