1

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

Data Engineer - Senior/Lead

Seattle, WA · On-site

$120K - $163K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where ... contracts) that the broader team can review, extend, and rely on. * Build the data pipelines ...

Big Data developer

Redmond, WA

$59.25 - $77/hr

... Contract (On W2) Need a Strong candidate with Big data and Kafka Provide thought leadership for the MFS data platform team and collaborate with cross-functional engineering teams to streamline or ...

Big Data developer

Redmond, WA · On-site

$59.25 - $77/hr

... Contract (On W2) Need a Strong candidate with Big data and Kafka • Provide thought leadership for the MFS data platform team and collaborate with cross-functional engineering teams to streamline or ...

AWS Data Engineer (Associate)

Seattle, WA · On-site +1

$130K - $156K/yr

Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract. This role sits in our Data Platform Modernization pillar: consolidating and ...

AWS Data Engineer (Associate)

Seattle, WA · On-site

$130K - $156K/yr

Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract. This role sits in our Data Platform Modernization pillar: consolidating and ...

AWS Data Engineer (Associate)

Seattle, WA · Remote

$117K - $140K/yr

Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract. This role sits in our Data Platform Modernization pillar: consolidating and ...

Showing results 41-60

Contract Data Engineering information

See Bothell, WA salary details

$49.7K

$145K

$198.4K

How much do contract data engineering jobs pay per year?

As of Aug 17, 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 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.

What are the key skills and qualifications needed to thrive as a contract data engineer?

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 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 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 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:

What cities near Bothell, WA are hiring for Contract Data Engineering jobs?

Cities near Bothell, WA with the most Contract Data Engineering job openings:

Infographic showing various Contract Data Engineering job openings in Bothell, WA as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, and 4% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution, with an average salary of $145,008 per year, or $69.7 per hour.

Data Engineer - Senior/Lead

Salesforce, Inc.

Seattle, WA • On-site

$120K - $163K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 10 days ago


Salesforce rating

8.1

Company rating: 8.1 out of 10

Based on 58 frontline employees who took The Breakroom Quiz

112th of 244 rated software companies


Job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

We are looking for a Data Engineer who thrives at the intersection of data engineering and analytics. In this role you will partner closely with data analysts and strategy experts to turn raw, distributed data into trusted, well-modeled datasets that power product strategy.
Our teams are made up of data scientists, engineers, and strategy lead who drive product strategy with data-driven insights. We work alongside executives, product managers, customer strategy, and sales strategy partners to discover new opportunities for growth, experiment with data, drive adoption, and surface insights that shape what we build next.

Responsibilities:

  • Sit alongside data scientists and strategy leads in planning, design reviews, and roadmap discussions - treating their questions and hypotheses as first-class inputs to architecture decisions.

  • Translate analytical and statistical requirements into well-performing SQL and scalable pipelines, and coach partners on patterns that scale (windowing, partitioning, incremental loads, idempotency).

  • Own the technical solution design and architecture of data acquisition and integration projects (batch and real-time), implementing a layered stack - raw cleansed curated semantic - that ensures high data quality, predictable freshness, and timely insights.

  • Craft design artifacts (functional design documents, data flow diagrams, data models, schema contracts) that the broader team can review, extend, and rely on.

  • Build the data pipelines, curated marts, semantic layers, and feature stores that let analysts answer business questions independently and let data scientists iterate on features and models without re-engineering raw sources.

  • Design tailored data structures (fact/dimension models, wide analytical tables) and end-to-end infrastructure for data science work: feature pipelines, model-ready training datasets, experimentation data, and the plumbing required for reliable ML and statistical workflows.

  • Take exploratory analyst/DS notebooks and prototypes and reinvent them as production-ready, monitored data flows.

  • Co-own data quality, lineage, and trust with your partners, and establish shared conventions - naming, documentation, testing, and review - that make handoffs low-friction.

  • Proactively identify gaps in data quality and performance, integrate data from disparate sources, and advocate for architectural and code improvements that improve execution speed and reliability.

  • Perform data profiling, sophisticated sampling, statistical testing, and reliability testing on data.

  • Serve as a domain expert and mentor for ETL/ELT design, dimensional modeling, and big data patterns; evaluate technology trade-offs and run proofs of concept to inform tooling decisions.

  • Bring strong SQL optimization and performance tuning expertise in high-volume, parallel-processing environments, working with the team's stack: SQL, Python, Airflow, AWS, Spark, Tableau, Hadoop (and adjacent tools like dbt, Snowflake, and Databricks where they fit).

  • Participate in the team's on-call rotation to address production data issues in real time and keep services operational and highly available for analytics and ML consumers.

Required Qualifications:

  • 8+ years of experience in data engineering.

  • Demonstrated experience working closely with data scientists and strategy analysts - not just shipping pipelines, but understanding how the data will be modeled, sampled, and analyzed downstream.

  • Build programmatic ETL/ELT pipelines with SQL-based technologies and platforms.

  • Solid understanding of databases and working with sophisticated datasets in Salesforce environment.

  • Data governance, verification, and data documentation using current and emerging tools and platforms.

  • Comfort across multiple technologies (Python, shell scripts) and the ability to translate business and analytical logic into well-performing SQL.

  • Comfort with tasks such as writing scripts, web scraping, and pulling data from APIs.

  • Experience automating data pipelines using scheduling and orchestration tools like Airflow.

  • Ability to adapt to changes in business direction and recognize when designs need to evolve.

  • Experience writing production-level SQL and a strong grasp of data engineering pipelines end-to-end.

  • Experience with the Hadoop ecosystem and similar frameworks.

  • Previous projects that show technical leadership across data lake, data warehouse, business intelligence, big data analytics, and enterprise-scale custom data products - ideally where analysts and data scientists were primary consumers.

  • Strong knowledge of data modeling techniques and high-volume ETL/ELT design.

  • Experience with version control systems (GitHub, Subversion) and deployment tools (e.g., CI/CD).

  • Ability to work effectively in an unstructured, fast-paced environment, both independently and as part of a cross-functional team, with a high degree of self-management, clear communication, and commitment to delivery timelines.

  • A technical degree is required.

Preferred Qualification:

  • Experience building feature stores, ML pipelines, or model-serving infrastructure in partnership with data scientists.

  • Experience designing semantic layers or metrics layers (e.g., dbt metrics, LookML, Cube) that empower analyst self-service.

  • Experience with experimentation platforms or A/B testing data infrastructure.

Unleash Your Potential

When you join Salesforce, you'll be limitless in all areas of your life. Our benefits and resources support you to find balance andbe your best, and our AI agents accelerate your impact so you cando your best. Together, we'll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what's possible - for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates' resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

What Salesforce employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom