1

Manager Data Engineering Jobs in Oregon (NOW HIRING)

OR · On-site

As the Senior Manager, Data Engineering, you will lead the strategy, architecture, and execution of Alto's data platform - ensuring that high-quality, trusted, and timely data fuels everything from ...

Responsibilities As a Manager, Data Management , you will lead the architecture, design, delivery ... Provide leadership and guidance to data engineers and developers in architecture, design ...

Data Engineering Manager

OR · On-site +1

$172K - $254K/yr

Collaborate with product managers, data analysts, and machine learning engineers to develop pipelines and ETL tasks in order to facilitate the extraction of insights. * Establish data architecture ...

Budget, Vendor, and Stakeholder Management (15%) - Own the data engineering budget, including cloud spend, tooling, and consulting partners. Lead vendor evaluation, selection, and management, and ...

Optimize performance, scalability, reliability, and cloud cost management. Deliver Trusted ... Master's degree preferred. * 10+ years of enterprise Data Engineering experience. * 5+ years ...

OR · On-site

We are looking for a highly skilled Senior Data Engineering Manager to lead one of our data engineering teams. This is a hands-on player-coach role for someone who can develop engineers, guide ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... In data engineering at PwC, you will focus on designing and building data infrastructure and ...

Data Engineer

Beaverton, OR · On-site

$119K - $143K/yr

Strong knowledge of data engineering principles, including data modeling, ETL and ELT design patterns, Data quality and observability, Metadata management, Data lifecycle management, Master Data ...

Data Engineer

Beaverton, OR

$119K - $143K/yr

Strong knowledge of data engineering principles, including data modeling, ETL and ELT design patterns, Data quality and observability, Metadata management, Data lifecycle management, Master Data ...

Data Engineer

Beaverton, OR · On-site

$119K - $143K/yr

Strong knowledge of data engineering principles, including data modeling, ETL and ELT design patterns, Data quality and observability, Metadata management, Data lifecycle management, Master Data ...

Data Engineer

Beaverton, OR

$119K - $143K/yr

Strong knowledge of data engineering principles, including data modeling, ETL and ELT design patterns, Data quality and observability, Metadata management, Data lifecycle management, Master Data ...

The Data Engineer works closely with the Technical Project Manager, data governance specialists, epidemiologists, research psychologists, tactical sports scientists, data scientists, and software ...

Lead and manage a team of data engineers in delivering quality code and building data products and use cases, fostering a culture of engineering excellence, accountability, and continuous improvement ...

OR

$446K - $752K/yr

We are looking for an experienced leader to help lead the Member Innovation Data Engineering team. This team will work in close partnership with Data Scientists and Product Managers to support new ...

Sr. Data Engineer

OR · On-site +1

$100K - $150K/yr

This role is remote-friendly and reports to the Manager, Data & Analytics Engineering. As a Sr. Data Engineer, your primary responsibility is to stay one step ahead of your fellow team members by ...

... Engineering, or Data Operations. * 3+ years of technical leadership experience managing engineering or operations teams. * Proven track record supporting enterprise-level production systems with high ...

Lead Data Engineer

Beaverton, OR · On-site

$119K - $143K/yr

Reporting to the Engineering Director, this team partners with data scientists, engineers, analysts, and product managers to build a cross-capability data foundation and a semantic layer that powers ...

$100K - $136K/yr

Expertise in Python for data engineering tasks, including data manipulation and workflow management. * Strong understanding of data modeling, data architecture, and best practices in data governance.

next page

Showing results 1-20

Manager Data Engineering information

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

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

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

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.
What are the most commonly searched types of Data Engineering jobs in Oregon? The most popular types of Data Engineering jobs in Oregon are:
What are popular job titles related to Manager Data Engineering jobs in Oregon? For Manager Data Engineering jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Manager Data Engineering jobs in Oregon look for? The top searched job categories for Manager Data Engineering jobs in Oregon are:
What cities in Oregon are hiring for Manager Data Engineering jobs? Cities in Oregon with the most Manager Data Engineering job openings:

Senior Manager, Data Engineering

Fuze Health

OR • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 21 days ago


Job description

Job Summary
At Fuze Health, we put patients first and tirelessly address the most pressing needs in healthcare. We empower millions to digitally connect with care providers, essential health resources and needed treatments - and enable care providers, employers, health plans and life sciences companies to meaningfully enhance quality, outcomes and value. We are dedicated to helping our partners evolve and modernize to meet emerging patient and marketplace needs.
Fuze Health's foundation is built upon the strategic combination of several proven, technology-powered innovators in the digital health, diagnostics, and pharmacy sectors. Our growing portfolio brings together the capabilities of industry leaders including LetsGetChecked, Truepill, and Alto Pharmacy, to create a distinctive, unified force in healthcare. Together, we have the shared vision, advanced capabilities and talented teams to deliver next-generation solutions that patients and healthcare partners need today and into the future.
Job Description
At Alto, we are transforming the pharmacy experience through intelligent, scalable technology. Data is foundational to how we serve patients, empower operators, and enable smarter decision-making across the business. As the Senior Manager, Data Engineering, you will lead the strategy, architecture, and execution of Alto's data platform - ensuring that high-quality, trusted, and timely data fuels everything from analytics and operations to product innovation and machine learning.
You will manage, build and lead a high-performing team responsible for designing resilient data pipelines, evolving our modern data stack, and establishing data engineering best practices. This role is equal parts technical leadership, organizational design, and cross-functional partnership - shaping how data is produced, governed, and consumed across a fast-growing, technology-driven healthcare organization.
Job Description

Key Responsibilities (see above)

Leadership & Vision

  • Lead, mentor, and grow a team of Data Engineers, fostering a culture of ownership, technical excellence, and continuous improvement.

  • Define and execute the long-term vision for Alto's data platform, ensuring alignment with company strategy and product roadmaps.

  • Partner with Product, Engineering, Data Science, Analytics, Finance, and Enterprise teams to prioritize and deliver high-impact data initiatives.

  • Establish clear career paths, performance standards, and hiring plans to scale the team thoughtfully and sustainably.

  • Build strong stakeholder trust by translating business needs into scalable data solutions.

Data Platform & Architecture

  • Own the design and evolution of Alto's data architecture, including ingestion, transformation, orchestration, storage, and serving layers.

  • Administer and maintain core platform tooling - including Fivetran, Airflow, dbt, Snowflake, and Looker - ensuring these systems operate as reliable, scalable, and secure infrastructure.

  • Provide a robust, well-governed platform foundation that enables Analytics to build and manage transformation logic within dbt, while enforcing standards for performance, testing, deployment workflows, access controls, and warehouse efficiency.

  • Ensure the underlying data platform reliably powers analytics, operational workflows, experimentation, and machine learning use cases - delivering trusted, well-documented, and production-grade data assets to both internal stakeholders and downstream systems.

  • Ensure the reliability, performance, and freshness of data pipelines through strong observability, lineage tracking, testing frameworks, and operational rigor.

  • Scale the platform to support increasing data volume, near-real-time use cases, and expanding business and regulatory complexity.

Data Governance, Quality & Operational Excellence

  • Evolve and strengthen existing standards for data governance, access control, privacy, and compliance within a regulated healthcare environment.

  • Refine and operationalize SLAs and performance metrics for data pipelines and platform reliability, ensuring clear accountability and transparency.

  • Enhance and scale current data quality monitoring and incident management practices to improve resilience, observability, and response times.

  • Continuously optimize infrastructure performance and cost efficiency through thoughtful architectural improvements and warehouse tuning.

Innovation & Cross-Functional Impact

  • Evaluate emerging technologies and evolve Alto's data stack to support streaming, near-real-time analytics, and scalable AI workflows.

  • Enable robust experimentation and measurement by providing reliable, well-instrumented, and production-grade data pipelines that Analytics, Data Science, and Product teams can confidently build upon.

  • Collaborate closely with Data Science and Machine Learning teams to ensure the platform scales alongside growing model and feature complexity, providing the infrastructure, environment consistency, and operational guardrails necessary for reliable training and production inference.

  • Drive adoption of best-in-class tooling and practices that improve developer velocity and reduce operational toil.

  • Cultivate a culture where data is treated as a product - with clear ownership, discoverability, and accountability.

Required Experience & Qualifications (see above)

Minimum Qualifications:

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or related field; advanced degree preferred.

  • 10+ years of experience in data engineering, platform engineering, or related data infrastructure roles.

  • 5+ years of experience leading and scaling high-performing technical teams.

  • Proven experience architecting, operating, and scaling modern cloud-based data platforms, including data ingestion, orchestration, cloud data warehouses, transformation frameworks, and semantic serving layers.

  • Strong expertise in data modeling principles, ELT architectures, and production-grade pipeline orchestration.

  • Hands-on experience with cloud environments (AWS, GCP, or Azure).

  • Proven track record owning platform reliability, including defining SLAs, implementing observability and data quality frameworks, and leading incident response and postmortems for production data systems.

  • Experience operating in high-growth, fast-paced technology organizations.

  • Strong communication skills with the ability to influence technical and non-technical stakeholders alike.

Preferred Qualifications:

  • Experience building data platforms in healthcare, pharmacy, fintech, or other regulated industries.

  • Familiarity with HIPAA and healthcare data privacy standards.

  • Experience supporting machine learning pipelines, feature engineering workflows, or feature stores.

  • Experience with streaming architectures (e.g., Kafka, Kinesis, Pub/Sub) and real-time analytics use cases.

  • Exposure to experimentation platforms and product analytics ecosystems.

  • Strong SQL and programming proficiency (e.g., Python, Scala, or similar).

  • Experience implementing data contracts and data product frameworks across domain teams.


Additional Information

Additional Physical Job Requirements

Physical requirements for this role include the ability to work at a computer terminal with monitor, keyboard and mouse for extended periods of time, stoop, bend, and reach for equipment and supplies, make frequent repetitive motions required to operate a computer that include the wrists, hands and fingers, and lift, carry, push, pull, and move light objects up to 20 pounds. The role also requires the ability to effectively communicate through verbal interactions, discern auditory information, and visually perceive details to perform essential job functions.

Consistent with the Americans with Disabilities Act (ADA) and similar applicable state laws, it is Fuze Health's policy to provide reasonable accommodation to enable qualified individuals with disabilities to perform essential job functions, unless such accommodation would cause an undue hardship.

Salary and Benefits

Salary Range: $180,000.00 - $225,000.00

Commission Eligible: No

Travel: No - Required up to 0% of the time

Location Requirement: Alto is limited to individuals residing in the following states: Arizona, Arkansas, California, Colorado, Florida, Kansas, Maryland, Missouri, Nevada, New Jersey, New York, North Carolina, Oregon, Pennsylvania, South Carolina, Tennessee, Texas, Washington (WA), and Wisconsin.

Employment Authorization Requirement: Applicants must be authorized to work for any employer in the U.S.

Benefits: Full-time employee benefits include: dental, vision, and multiple group medical plans to choose from, a 401(k) retirement savings plan, group life insurance, accidental death and dismemberment (AD&D) insurance, flexible spending account (FSA) and health savings account (HSA), commuter benefits, employer-paid short-term (STD) and long-term disability (LTD) insurance, and additional supplemental insurance plans (spouse life insurance, legal insurance, an employee assistance program, home health testing kits, and a fertility medication discount program). Employees are also provided flexible vacation time, accrued paid sick time, 10 paid holidays, (2 floating holidays for full time non-exempt employees) , and eight weeks of paid parental leave for eligible employees, additional paid weeks for the birthing parent, 4 weeks paid caregiver leave, and a Lifestyle Spending Account allowance each month.

More Benefits Information Here: Fuze Health Benefits Site


#LI-Remote

Equal Opportunity Employer

Fuze Health is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, gender identity, sexual orientation, age, disability, veteran status, or any other legally protected basis. If you have a disability and require reasonable accommodation during any portion of the application or hiring process, please contact us at talent@fuzehealth.com.


Fuze Health considers qualified applicants with arrest or conviction records for employment and conducts background checks consistent with applicable law, including the California, Los Angeles County, San Francisco, Philadelphia, and New York City Fair Chance laws. We are an E-Verify participating company.


Use of Automated Decision Tools

Fuze Health recruiters and hiring managers may use automated decision tools to help identify candidates who match the stated job requirements, and to what extent. These tools are designed to help ensure fairness in all aspects of the hiring process by providing recruiters and hiring managers with data-backed insights based on information provided in your resume, including work experience, education, and other skills. Fuze Health does not use automated decision tools to make hiring decisions; hiring decisions always involve human review and input. If you have any questions or would like to request an alternative process, please contact us at talent@fuzehealth.com.


Privacy Notice

To learn about Fuze Health's privacy practices, including compliance with applicable privacy laws, please read our Privacy Notice for Job Applicants.