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Manager Data Analytics Engineer Jobs in Hermiston, OR

Sr. Data Engineer

Richland, WA · On-site

$119K - $143K/yr

Under the general supervision of the Data Analytics & Governance Manager/Team Leader, the Sr. Data Engineer plays a key role in supporting the enterprise data infrastructure and systems required for ...

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Manager Data Analytics Engineer information

See Hermiston, OR salary details

$46.3K

$135K

$184.7K

How much do manager data analytics engineer jobs pay per year?

As of Jul 26, 2026, the average yearly pay for manager data analytics engineer in Hermiston, OR is $135,014.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,200.00 and $143,100.00 per year, depending on experience, location, and employer.

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

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

How does a Manager Data Analytics Engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

What are the key skills and qualifications needed to thrive as a Manager Data Analytics Engineer, and why are they important?

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is a Manager Data Analytics Engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.
What job categories do people searching Manager Data Analytics Engineer jobs in Hermiston, OR look for? The top searched job categories for Manager Data Analytics Engineer jobs in Hermiston, OR are:
What cities near Hermiston, OR are hiring for Manager Data Analytics Engineer jobs? Cities near Hermiston, OR with the most Manager Data Analytics Engineer job openings:
Infographic showing various Manager Data Analytics Engineer job openings in Hermiston, OR as of June 2026, with employment types broken down into 2% As Needed, 79% Full Time, 17% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $135,014 per year, or $64.9 per hour.
Sr. Data Engineer

Sr. Data Engineer

GESA CREDIT UNION

Richland, WA • On-site

$119K - $143K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago


Gesa Credit Union rating

7.0

Company rating: 7.0 out of 10

Based on 11 frontline employees who took The Breakroom Quiz


Job description

Take a leap and join our team!

At Gesa, we believe in the power of our people. Coming from all walks of life, our team members’ individual stories and unique experiences are our most valuable asset. But it’s how we come together, igniting our collective compassion and commitment to empowering our communities, that makes us succeed. Because we know we go further when we go together.

Here you can join a team who is passionate about serving others, has a desire to do good, and shares a deep love of people. You can engage in meaningful work that impacts your community. You can challenge yourself and grow in your career. And, you can rest assured that your wellbeing and prosperity are our priority. 

Get to know us:  About - Gesa Credit Union

Role Summary:

Under the general supervision of the Data Analytics & Governance Manager/Team Leader, the Sr. Data Engineer plays a key role in supporting the enterprise data infrastructure and systems required for data storage, processing, and analysis. While the third-party vendor is responsible for designing the core data warehouse and managing data ingestion from major systems, the Sr. Data Engineer will assist the data warehouse vendor with the establishment of new data sources and provide support for any maintenance and troubleshooting required. This includes focusing on integrating smaller or supplemental data sources into the Azure-based data warehouse and Databricks analytics platform, collaborating with internal teams to identify, model, and automate the ingestion of these data sources, and ensuring they meet organizational standards for data quality, governance, and security. Additionally, the Sr. Data Engineer partners closely with business leaders and executives to help define and advance the vision for managing data as a strategic business asset, aligning data management practices with organizational goals and driving value through effective data stewardship.

What You Will Be Doing:
  1. Represent the Data Intelligence department in projects and committees as assigned
  2. Lead the design, development, and optimization of data pipelines for extracting, transforming, and loading data from diverse sources into the third-party data warehouse on Azure
  3. Collaborate with data analysts, BI analysts, data quality and data stewards, and IT professionals to develop and maintain scalable data models and analytical solutions
  4. Integrate data from databases, APIs, and external systems, ensuring consistency, integrity, and quality throughout the process
  5. Implement and monitor data governance frameworks, including data validation, cleansing, aggregation, and enrichment techniques
  6. Establish and enforce data quality checks, validations, and compliance with policies and procedures
  7. Optimize data processing workflows for performance, scalability, and efficiency; resolve bottlenecks and enhance query performance
  8. Design, develop, and maintain scalable data engineering solutions using Databricks, including Spark-based transformations, notebooks, and jobs
  9. Apply Databricks best practices for cluster configuration, job orchestration, performance tuning, and cost-aware design
  10. Implement medallion-style data architectures (Bronze, Silver, Gold) to support governed and analytics-ready datasets
  11. Enable and optimize data pipelines to support AI, machine learning, and advanced analytics use cases, fostering innovation across the organization
  12. Identify opportunities to leverage emerging technologies and innovative data engineering approaches for enhanced business insights and improved decision-making
  13. Support the ongoing strategic planning and monitoring process for data intelligence and data governance
  14. Educate and train stakeholders on data warehouse solutions, data governance, and best practices
  15. Maintain expert-level knowledge of core operating systems, data warehouse platforms, and data intelligence tools
About You:
  1. Advanced knowledge of Databricks for data engineering workloads, including Apache Spark, job orchestration and best practices such as layered data architectures, incremental processing, and optimization techniques
  2. Ability to comfortably utilize modern cloud-based data integration tools within Azure (e.g., Azure Data Factory, Databricks, Synapse Analytics)
  3. Proficiency with a range of programming and scripting languages commonly used in data engineering, including SQL, Python, Scala, Java, Bash or PowerShell, and R.
  4. Advanced understanding of relational and NoSQL databases, data modeling, and data integration
  5. Ability to collaborate across teams and communicate technical concepts to diverse stakeholders
  6. Strong analytical, problem-solving, and debugging skills
  7. Excellent business acumen and interpersonal skills
  8. Commitment to continual process improvement and adherence to data governance standards
  9. Demonstrated leadership capabilities, including coaching and mentoring team members to foster professional growth and promote a collaborative work environment.
What You Will Need:
  1. Bachelor’s degree in Computer Science, Data Science, Software Engineering, Information Systems, or related quantitative field; Master’s degree preferred
  2. Minimum of six (6) years of experience in data engineering or data management disciplines required
  3. Experience designing and operating data pipelines using Databricks in a cloud-based analytics environment preferred
  4. Experience in financial institution environments preferred
Our Team Member Value Proposition:

In exchange for bringing your talent to Gesa, here are a just a few of the benefits and perks we offer:

  • Competitive Pay
  • Medical, Dental, Vision, and Life Insurance 
  • 20 days/year of Paid Time Off – Plus 10 Paid Holidays!
  • 401(k) Match
  • Incentive Program
  • Tuition Assistance and Student Loan Repayment
  • Commuter Benefits
  • Paid Time Off to Volunteer in the Community
  • Product discounts
  • Engaging Work Environment
  • Rewards and Recognition Programs
Full Salary Range:
Richland, WA: $97,069.57-$161,782.61
Spokane WA: $97,069.57-$161,782.61
Renton, WA: $117,365.93-$195,609.89

*While our full pay range is listed, most new team members typically start between the minimum and midpoint based on their experience and qualifications.  This approach gives room to grow within the role as your career progresses with us!"

Get wise to what’s possible with a career at Gesa. Join us!

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact the HR Department at (509) 378-3100 or hrmail@gesa.com to request an accommodation.

Gesa Credit Union reserves the right to revise or change the job description as the need arises. This job description is not all inclusive of total job responsibilities nor does it constitute a written or implied contract of employment.

Selected candidate(s) must be able to pass a pre-employment credit/background check.

Gesa Credit Union is an Equal Opportunity Employer and strong advocate of workforce diversity. Race/Color/Gender/Sexual Orientation/Gender Identity/Religion/National Origin/Disability/Veteran.

Equal Employment Opportunity (gesa.com)


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