Data Platform Engineer Jobs in Washington
Data Platform Engineer jobs in Washington are among the most active in the country, concentrated in cloud infrastructure, enterprise data engineering, and analytics platform development across the Seattle metro, Bellevue, and Redmond. Demand runs from entry-level data engineers to principal platform architects, driven by major employers including Microsoft, Amazon, and Boeing. The most sought-after specializations in Washington are cloud-native pipeline architecture, real-time data streaming, and data lakehouse design. Find a role that fits below and apply directly.
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Now Brewing – senior engineer! #tobeapartner
From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
As a Starbucks senior data & AI engineer, you’ll help turn trusted data and emerging AI capabilities into practical solutions for teams across Starbucks.
You’ll join the Enterprise Data & Analytics Platform team to build reliable data services and AI-enabled analytics experiences. Working primarily in Databricks platform, you’ll design, develop, test, deploy, and support pipelines and tools that power continuous data processing, exploration, preparation, real-time analytics, trusted self-service insights, and AI-assisted decision making. The role combines hands-on engineering with close collaboration and a shared commitment to security, quality, the partner experience, and Starbucks guiding principles.
What you’ll do:
Data Engineering
- Build dependable Lakehouse solutions with Databricks, Delta Lake, PySpark, and SQL, applying strong practices for orchestration, medallion architecture, data quality, schema evolution, and production support.
- Develop and support highly available batch, distributed, incremental, and real-time pipelines that power enterprise analytics, AI/BI, and AI-assisted business workflows.
- Work with upstream and downstream engineering teams to integrate source systems, standardize data contracts, improve lineage and observability, and make data products reliable and reusable for business and AI needs.
AI Engineering
- Design, build, and run Databricks Genie so partners can ask questions and receive trusted answers from governed enterprise data.
- Create and maintain Genie spaces, semantic models, curated datasets, dashboards, and supporting pipelines, with clear ownership, documentation, and release practices.
- Create practical ways to evaluate Genie, RAG, and agentic workflows using golden datasets, groundedness checks, regression testing, answer-quality scores, latency and cost tracking, and user feedback.
- Improve the quality of Genie and similar tools by tracing issues across prompts, semantic definitions, generated SQL, joins, metric logic, access rules, and source data.
- Build responsible AI and safety into every solution through access-aware grounding, careful handling of sensitive data, guardrails, auditability, human review, and proactive risk mitigation.
Engineering Excellence & Collaboration
- Use Unity Catalog to manage access controls, lineage, tagging, certified data products, semantic definitions, retention, and documentation so enterprise data stays secure, discoverable, reusable, and supportable.
- Investigate data and platform issues, tune performance, weigh trade-offs, and implement lasting solutions rather than short-term fixes.
- Create reliable delivery and support practices for Databricks notebooks, jobs, workflows, semantic artifacts, and AI/BI resources using CI/CD, testing, monitoring, observability, cost attribution, Declarative Automation Bundles, GitHub Actions, and environment-based release controls.
- Partner with engineering, analytics, data science, product, security, and business teams to turn real business questions into reusable metrics, certified tables, governed experiences, and dependable data contracts.
- Improve and document team coding standards, reusable frameworks, deployment patterns, and monitoring practices, and share Databricks, Genie, and AI engineering best practices across the organization.
- Mentor and support other engineers by sharing practical experience in agile delivery, DevOps, data engineering, and AI engineering.
We’d love to hear from people with:
- A bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, Data Science, Information Systems, or a related quantitative field.
- 4+ years of industry experience in data engineering, analytics engineering, AI engineering, or enterprise data-platform delivery.
- 4+ years of hands-on experience building and operating Databricks Lakehouse solutions in production. This includes experience with Databricks Workflows, notebooks, jobs, Delta Lake, Spark, PySpark, SQL, Python, data modeling, data quality, and production support.
- 1+ year designing, configuring, tuning, and supporting Databricks Genie or a similar natural-language analytics platform, with experience in semantic context, AI/BI experiences, and governed self-service analytics.
- 3+ years working with Unity Catalog governance, permissions, lineage, tagging, table certification, and governed access patterns.
- 4+ years working with SQL, dimensional and semantic modeling, metric definition, source-of-truth identification, join accuracy, and business-logic validation.
- 4+ years delivering ETL/ELT pipelines, medallion architecture, data-quality frameworks, orchestration, schema evolution, and ongoing data-product support.
- 3+ years using Declarative Automation Bundles and GitHub Actions to support CI/CD and environment promotion, including testing, monitoring, observability, and cost attribution.
- 4+ years partnering with data science, analytics, product, security, platform engineering, and business teams to deliver production outcomes.
- A customer-focused mindset, strong analytical problem-solving skills, and the ability to explain technical trade-offs clearly.
Preferred:
- Experience using AI-assisted engineering tools and techniques to accelerate data engineering, improve developer productivity, and strengthen the quality of production solutions.
- Familiarity with MLflow, Mosaic AI, model serving, vector search, RAG patterns, or agent-oriented AI workflows.
- Experience applying business knowledge and sound engineering judgment in cross-functional work.
- Experience working in retail or another high-volume customer environment.
- Familiarity with Design Thinking practices.
- Experience delivering production-grade data or AI platforms at scale.
As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor’s degree through Arizona State University’s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com.
- If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.
The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate.
Join us and inspire with every cup. Apply today!
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law.
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances.
Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.
Now Brewing – senior engineer! #tobeapartner
From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
As a Starbucks senior data & AI engineer, you’ll help turn trusted data and emerging AI capabilities into practical solutions for teams across Starbucks.
You’ll join the Enterprise Data & Analytics Platform team to build reliable data services and AI-enabled analytics experiences. Working primarily in Databricks platform, you’ll design, develop, test, deploy, and support pipelines and tools that power continuous data processing, exploration, preparation, real-time analytics, trusted self-service insights, and AI-assisted decision making. The role combines hands-on engineering with close collaboration and a shared commitment to security, quality, the partner experience, and Starbucks guiding principles.
What you’ll do:
Data Engineering
- Build dependable Lakehouse solutions with Databricks, Delta Lake, PySpark, and SQL, applying strong practices for orchestration, medallion architecture, data quality, schema evolution, and production support.
- Develop and support highly available batch, distributed, incremental, and real-time pipelines that power enterprise analytics, AI/BI, and AI-assisted business workflows.
- Work with upstream and downstream engineering teams to integrate source systems, standardize data contracts, improve lineage and observability, and make data products reliable and reusable for business and AI needs.
AI Engineering
- Design, build, and run Databricks Genie so partners can ask questions and receive trusted answers from governed enterprise data.
- Create and maintain Genie spaces, semantic models, curated datasets, dashboards, and supporting pipelines, with clear ownership, documentation, and release practices.
- Create practical ways to evaluate Genie, RAG, and agentic workflows using golden datasets, groundedness checks, regression testing, answer-quality scores, latency and cost tracking, and user feedback.
- Improve the quality of Genie and similar tools by tracing issues across prompts, semantic definitions, generated SQL, joins, metric logic, access rules, and source data.
- Build responsible AI and safety into every solution through access-aware grounding, careful handling of sensitive data, guardrails, auditability, human review, and proactive risk mitigation.
Engineering Excellence & Collaboration
- Use Unity Catalog to manage access controls, lineage, tagging, certified data products, semantic definitions, retention, and documentation so enterprise data stays secure, discoverable, reusable, and supportable.
- Investigate data and platform issues, tune performance, weigh trade-offs, and implement lasting solutions rather than short-term fixes.
- Create reliable delivery and support practices for Databricks notebooks, jobs, workflows, semantic artifacts, and AI/BI resources using CI/CD, testing, monitoring, observability, cost attribution, Declarative Automation Bundles, GitHub Actions, and environment-based release controls.
- Partner with engineering, analytics, data science, product, security, and business teams to turn real business questions into reusable metrics, certified tables, governed experiences, and dependable data contracts.
- Improve and document team coding standards, reusable frameworks, deployment patterns, and monitoring practices, and share Databricks, Genie, and AI engineering best practices across the organization.
- Mentor and support other engineers by sharing practical experience in agile delivery, DevOps, data engineering, and AI engineering.
We’d love to hear from people with:
- A bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, Data Science, Information Systems, or a related quantitative field.
- 4+ years of industry experience in data engineering, analytics engineering, AI engineering, or enterprise data-platform delivery.
- 4+ years of hands-on experience building and operating Databricks Lakehouse solutions in production. This includes experience with Databricks Workflows, notebooks, jobs, Delta Lake, Spark, PySpark, SQL, Python, data modeling, data quality, and production support.
- 1+ year designing, configuring, tuning, and supporting Databricks Genie or a similar natural-language analytics platform, with experience in semantic context, AI/BI experiences, and governed self-service analytics.
- 3+ years working with Unity Catalog governance, permissions, lineage, tagging, table certification, and governed access patterns.
- 4+ years working with SQL, dimensional and semantic modeling, metric definition, source-of-truth identification, join accuracy, and business-logic validation.
- 4+ years delivering ETL/ELT pipelines, medallion architecture, data-quality frameworks, orchestration, schema evolution, and ongoing data-product support.
- 3+ years using Declarative Automation Bundles and GitHub Actions to support CI/CD and environment promotion, including testing, monitoring, observability, and cost attribution.
- 4+ years partnering with data science, analytics, product, security, platform engineering, and business teams to deliver production outcomes.
- A customer-focused mindset, strong analytical problem-solving skills, and the ability to explain technical trade-offs clearly.
Preferred:
- Experience using AI-assisted engineering tools and techniques to accelerate data engineering, improve developer productivity, and strengthen the quality of production solutions.
- Familiarity with MLflow, Mosaic AI, model serving, vector search, RAG patterns, or agent-oriented AI workflows.
- Experience applying business knowledge and sound engineering judgment in cross-functional work.
- Experience working in retail or another high-volume customer environment.
- Familiarity with Design Thinking practices.
- Experience delivering production-grade data or AI platforms at scale.
As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor’s degree through Arizona State University’s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com.
- If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.
The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate.
Join us and inspire with every cup. Apply today!
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law.
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances.
Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.
See All 29 Data Platform Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find Data Platform Engineer JobsData Platform Engineer Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
Data Platform Engineer Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Banking & Financial Services
- Science & Research
- Technology & Software
- Investment & Asset Management
- Consulting & Professional Services
What Washington Employers Look For
The qualifications that appear most often in data platform engineer jobs across Washington.
- Bachelor's degree in Computer Science, Data Engineering, or a closely related field
- Proficiency in cloud platforms such as Azure, AWS, or Google Cloud
- Experience building and maintaining data pipelines using Apache Spark or Apache Kafka
- Hands-on expertise with data warehousing tools such as Snowflake, Databricks, or Redshift
- Strong programming skills in Python, Scala, or SQL for data transformation and orchestration
- Familiarity with infrastructure-as-code tools such as Terraform or Pulumi in production environments
Data Platform Engineer Jobs in Washington: Frequently Asked Questions
How do you become a data platform engineer in Washington?
Data platform engineering has no state-issued license in Washington, so the path runs through education and demonstrated technical skill. Most Washington employers expect a bachelor's degree in Computer Science, Software Engineering, or Information Systems, though strong candidates also come from mathematics or statistics programs. Building a portfolio of real pipeline and warehouse projects, earning cloud certifications from Azure or AWS, and contributing to open-source data tools are the credentials that move candidates to the top of Washington hiring queues.
How much do data platform engineers make in Washington?
Data platform engineers in Washington earn a median of about $128,760 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $101,970 for the lowest 10% to over $195,590 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data platform engineers in Washington?
Employers hiring data platform engineers in Washington right now include Amazon, Microsoft, and Airwallex, based on current listings on Migrate Mate as of November 2026. Washington's density of cloud-native technology companies and large enterprise headquarters makes it one of the most consistent states for sustained data platform hiring across multiple industries.
Which Washington cities have the most data platform engineer jobs?
Seattle, Redmond, and Bellevue have the most data platform engineer openings in Washington. Seattle anchors the market as home to Amazon's global headquarters and a deep ecosystem of cloud and analytics companies, while Bellevue and Redmond draw substantial hiring through Microsoft's campus and the enterprise software firms that cluster around it.
Are there remote data platform engineer jobs in Washington?
Yes, and more than most fields. About 55% of data platform engineer openings tied to Washington are remote or hybrid as of November 2026, reflecting how thoroughly the work lives in cloud consoles and code repositories rather than on-site infrastructure. Pipeline development, data modeling, and platform architecture work are the areas where Washington employers most consistently offer location flexibility.
How can I get hired as a data platform engineer in Washington with little or no experience?
The most realistic entry path is through a data analyst or business intelligence developer role at a Washington employer, then moving laterally into platform engineering once you have pipeline exposure. Companies such as Microsoft and Amazon run structured early-career programs and university recruiting that place new graduates into data engineering rotations. Building personal projects on Azure or AWS, contributing to open-source tools like Apache Airflow, and earning an associate-level cloud certification give candidates without professional experience a concrete edge in Washington applications.
Where can I find and apply to data platform engineer jobs in Washington?
You can find and apply to data platform engineer jobs in Washington on Migrate Mate, which lists current Washington openings updated regularly. Find the roles that fit your experience and location preference and apply directly to each one.
See All 29 Data Platform Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find Data Platform Engineer Jobs