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Contract Data Engineering Jobs in Bothell, WA (NOW HIRING)

Senior Data Engineer

Redmond, WA · On-site

$118K - $161K/yr

Partner with PM and engineering to make data contracts, freshness, drift signals, and offline/online consistency first-class concerns. * Design and architecture: Lead design discussions for your ...

... and contract lifecycle management (CLM). What you'll do Docusign's Product Data Science team is ... Partner closely with the product managers, user researchers, engineers, and leadership to capture ...

Contract Duration: 10 Months * Ability to thrive on a highly technical team in a 7x24x365 NOC ... Knowledge of Engineering systems such as TIRKS, Worddoc, Granite * Previous Mobility RAN transport ...

... 2025 Position Type Contract Location : Bellevue, WA Remote Work100% Primary SkillsAWS Cloud ... Overall, 8-10 years of solid experience in the areas of data engineering / machine learning / data ...

Palantir Developer

Seattle, WA · Remote

$60 - $70/hr

... on engineering expertise, data platform experience, and client-facing communication skills. This is a remote role, no visa sponsorship available, and contract to hire role. Client Details The ...

New

SDET

Seattle, WA · On-site +1

$57 - $73.50/hr

SDET Location - Seattle, WA - Remote Contract About the Role: We are seeking a highly skilled SDET to join our Master Data Management (MDM) team called PLIM. The ideal candidate will have strong ...

Data Governance enforcement and tooling (Data Contracts, RBAC mechanisms). * Building self-service tools for Data Owners and Data Engineers. What You'll Do As an emerging leader within our team, you ...

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Contract Data Engineering information

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$49.7K

$145K

$198.4K

How much do contract data engineering jobs pay per year?

As of Jun 19, 2026, the average yearly pay for contract data engineering in Bothell, WA is $145,008.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,000.00 and $153,700.00 per year, depending on experience, location, and employer.

What is the difference between Contract Data Engineering vs Data Analyst?

AspectContract Data EngineeringData Analyst
Required SkillsSQL, Python, ETL, cloud platforms, data pipeline developmentSQL, Excel, data visualization, reporting tools
Work EnvironmentProject-based, technical teams, cloud or on-premises infrastructureBusiness units, reporting teams, often in office or remote
Industry UsageTech, finance, healthcare, retailMarketing, finance, healthcare, retail

Contract Data Engineers focus on building and maintaining data pipelines and infrastructure, requiring technical skills in programming and cloud platforms. Data Analysts interpret data, create reports, and visualize insights, often using different tools. While both roles work with data, Contract Data Engineering is more technical and infrastructure-oriented, whereas Data Analysts focus on data interpretation and business insights.

What is the salary of a freelance data engineer?

The salary of a freelance data engineer varies widely based on experience, project complexity, and location, but typically ranges from $50 to $150 per hour. Experienced professionals with skills in cloud platforms, data pipelines, and programming languages like Python or SQL tend to command higher rates. Freelancers often set their rates based on project scope and client requirements.

What engineers make $500,000?

Senior data engineers, especially those with extensive experience, specialized skills in cloud platforms, and expertise in big data tools, can earn $500,000 or more annually. High compensation is often associated with leadership roles, consulting, or working in high-demand industries such as finance or technology. Achieving this level typically requires advanced certifications, a strong track record, and sometimes equity or performance bonuses.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their skills in programming, database management, and cloud platforms remain in high demand. AI tools serve as complements that enhance efficiency rather than substitutes for the core responsibilities of data engineers.

What is contract data engineering?

Contract data engineering refers to hiring data engineers on a temporary or project basis, rather than as full-time employees. Contract data engineers are responsible for designing, building, and maintaining data pipelines, databases, and other infrastructure to support data analytics and business needs. Companies often hire contract data engineers to handle specific projects, scale up teams quickly, or bring in specialized skills for a limited time. This arrangement offers flexibility for both the company and the engineer, and is common in industries with fluctuating data workloads or short-term projects.

Is contract engineering a good career?

Contract data engineering involves short-term or project-based work focused on designing, building, and maintaining data pipelines and systems. It offers flexibility and diverse experience but may lack long-term job security and benefits compared to permanent roles. Success in this career often depends on technical skills, certifications, and the ability to adapt to different environments.

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

To thrive as a Contract Data Engineer, you need strong proficiency in data modeling, ETL processes, and programming languages such as Python or SQL, often supported by a degree in computer science or a related field. Familiarity with big data platforms (e.g., Hadoop, Spark), cloud services (AWS, Azure, GCP), and relevant certifications like Google Cloud Professional Data Engineer are typically required. Excellent problem-solving, adaptability, and effective communication are crucial soft skills in this role. These competencies enable efficient project delivery, seamless collaboration with stakeholders, and the ability to quickly adapt to new technical environments and client requirements.

What are some common challenges faced by contract data engineers and how can they be addressed?

Contract data engineers often face the challenge of quickly familiarizing themselves with a company's existing data infrastructure and processes. Since contracts are typically short-term, there is limited time to onboard, understand unique data pipelines, and build relationships with stakeholders. To address this, successful contract data engineers proactively communicate with team members, document their work thoroughly, and leverage their prior experience with a variety of tools and platforms. Flexibility and strong problem-solving skills are essential for adapting to new environments and delivering results efficiently.
What are the most commonly searched types of Data Engineering jobs in Bothell, WA? The most popular types of Data Engineering jobs in Bothell, WA are:
What are popular job titles related to Contract Data Engineering jobs in Bothell, WA? For Contract Data Engineering jobs in Bothell, WA, the most frequently searched job titles are:
What job categories do people searching Contract Data Engineering jobs in Bothell, WA look for? The top searched job categories for Contract Data Engineering jobs in Bothell, WA are:
Infographic showing various Contract Data Engineering job openings in Bothell, WA as of June 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $145,008 per year, or $69.7 per hour.
Senior Data Engineer

Senior Data Engineer

Microsoft

Redmond, WA • On-site

$118K - $161K/yr

Full-time

Posted 8 days ago


Microsoft rating

8.6

Company rating: 8.6 out of 10

Based on 125 frontline employees who took The Breakroom Quiz

49th of 191 rated software companies


Job description

Overview
If you love the pursuit of excellence and are inspired by the challenges that come through driving innovations that impact how the world lives, works and plays, then we invite you to learn more about Microsoft Business Operations (MBO) - and the value we deliver across Microsoft and to our customers and partners. We offer unique opportunities to work on interesting global projects in an environment that appreciates diversity, focuses on talent development and recognizes and rewards great work.
As a Senior Data Engineer, you'll build and operate the platforms that power how Microsoft does business-solving complex, high-impact problems at global scale and shipping technology used every day across the company.
Position Description:
As a Senior Data Engineer, you will design, build, and operate software that helps teams launch and manage products across Microsoft. You will work closely with partner engineers, product managers, and stakeholders to deliver reliable, secure, and scalable services, translating customer and business needs into high-quality engineering solutions.
In this role, you will drive engineering excellence through strong design skills, clean implementation, and a focus on operational quality. You will contribute to architecture and technical direction, review code and designs, and use AI-assisted development tools (e.g., GitHub Copilot, agentic coding workflows, GenAI-based code review and test generation) in a disciplined, production-grade way - taking full responsibility for the quality and safety of AI-generated artifacts and applying Responsible AI practices. You will improve developer velocity through automation, tooling, and AI-powered workflows, use telemetry to troubleshoot issues and continuously improve performance, reliability, and cost, and - where applicable - help integrate AI capabilities such as LLMs, agents, and model-backed features into production systems. You will also mentor others and help raise the team's engineering bar through collaboration, experimentation with new AI practices, and a growth mindset.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
As a Senior Data Engineer, you will own the end-to-end engineering lifecycle for key components and services-designing, coding, testing, deploying, and operating solutions that are secure, reliable, and maintainable.
  • AI-native development: Use AI tools across the full SDLC in a disciplined way. Own the quality of AI-generated requirements, designs, and code - yours and your teammates' - and apply Responsible AI practices.
  • Data for AI: Build the training, feature, retrieval, grounding, and evaluation datasets that LLMs, and agents depend on. Partner with PM and engineering to make data contracts, freshness, drift signals, and offline/online consistency first-class concerns.
  • Design and architecture: Lead design discussions for your project area, evaluate tradeoffs across batch vs. streaming, warehouse vs. lakehouse, ELT vs. ETL, and storage choices for analytical, feature, and vector workloads. Own architectural decisions with minimal oversight.
  • Customer requirements: Partner with PM and engineering to define data requirements; ensure feedback loops on data quality, usage, model performance, and downstream product impact are in place.
  • High-quality code: Write extensible, secure, performant code for pipelines, transformations, and supporting services. Apply modern patterns including GenAI-assisted development. Drive code reviews and best practices at the product level.
  • Testing and quality: Own the test strategy for your area, including data contract tests, schema validation, freshness checks, distribution and drift monitoring, and offline/online parity. Improve the test suite and use AI tools for test automation.
  • Dependencies and coordination: Identify cross-team data dependencies, manage upstream producer and downstream consumer impact, and resolve conflicts when semantics or schemas change in ways that affect models or downstream products.
  • Planning: Drive your workgroup's project and release plans. Break work into a roadmap including backfills, migrations, and model-impacting changes, and coach others on estimation.
  • Experimentation: Design and run experiments - A/B tests, shadow pipelines, offline replays, evaluation harnesses - and interpret results to guide ship decisions for data and for the models that depend on it.
  • Deployment and velocity: Drive deployment automation toward zero-touch; strengthen CI/CD for data systems, including reversible migrations, safe backfills, and controlled rollouts of semantic changes.
  • Live site: Participate in on-call rotation as a DRI for data pipelines and serving paths. Use telemetry to diagnose, mitigate, and lead retrospectives. Drive metrics that improve reliability, data quality, and customer impact - including model and agent behavior traced back to data.
  • Security, privacy, accessibility: Apply security-as-code, threat modeling, and breach-drill practices. Ensure AI safety controls and data governance for the AI features your data supports. Meet privacy, compliance, and accessibility standards.
  • Leadership: Lead by example. Mentor engineers on data engineering craft and AI fluency, raise the team's bar, and foster an inclusive culture.

Qualifications
Required Qualifications:
  • Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.

Preferred Qualifications:
  • Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 8+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.
  • 2+ years experience with data governance, data compliance and/or data security.
  • 4+ years of hands-on software development experience in one or more general purpose programming languages (e.g., C#, Java, C++, Python, JavaScript/TypeScript).
  • Hands-on experience designing and operating production data pipelines and platforms at scale.
  • Working understanding of how GenAI systems consume data - training datasets, features and labels, embeddings, retrieval and grounding data, evaluation harnesses, and the data-side failure modes that drive model and agent regressions.
  • Hands-on experience using AI-assisted development tools (e.g., GitHub Copilot, agentic coding workflows, GenAI-based code review and test generation) in a disciplined, production-grade way.
  • Experience integrating AI capabilities (LLMs, agents, model-backed features) into production systems, including familiarity with Responsible AI principles and applying AI safety controls in production.
  • Experience owning a feature area end-to-end, from design through deployment, monitoring, and on-call ownership.
  • Experience designing and operating large-scale distributed data systems in a cloud environment (e.g., Azure), including data model and pipeline design, performance tuning, and cost optimization.
  • Engineering fundamentals: data structures and algorithms, object-oriented and systems design, and building resilient services (reliability, availability, scalability).
  • Experience with DevOps practices and tooling (CI/CD, infrastructure as code, monitoring and alerting, incident response) and a track record of driving toward zero-touch deployment.
  • Experience building observable systems: designing telemetry, metrics, and dashboards - including data quality and drift signals - that drive reliability, performance, and customer-impact decisions.
  • Experience building secure software, including secure coding practices, threat modeling, premortems, and privacy/compliance considerations relevant to data systems.
  • Demonstrated technical leadership through design reviews, mentoring, and driving improvements to code quality and engineering processes.
  • Experience collaborating in cross-functional and communicating technical concepts clearly to engineering, product, and executive audiences.

Data Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800.00 - $234,700.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200.00 - $261,000.00 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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About Microsoft

Sourced by ZipRecruiter

Our infrastructure is comprised of a large global portfolio of more than 100 datacenters and 1 million servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide. With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Redmond, WA, US

Year founded

1975

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