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Contract Data Engineering Jobs in Oregon (NOW HIRING)

OR · On-site

$114K - $137K/yr

Partner with product, bioinformatics, analytics, AI, software engineering, and infrastructure teams to define requirements, priorities, data contracts, and delivery models, and translate them into ...

$122K - $180K/yr

Minimum of 5 years of hands-on data engineering experience in enterprise or DoD environments ... contract requirements, and candidate qualifications, such as education, experience, skills, and ...

OR · On-site

$114K - $137K/yr

We are seeking a Looker Data Engineer for a project-based assignment to support a key client ... Contract * Applicants must be authorized to work for ANY employer in the U.S. We are unable to ...

OR · On-site

... offshore contract team, and enabling our data engineering teams to move fast with confidence. You will be a key driver of technical strategy and execution without direct people management ...

OR · On-site

$126K - $166K/yr

You'll work closely with Data Engineering, Analytics, Client Success, and Implementation teams to define what the future of data integration at Transcarent looks like, from strengthening core ...

Senior Data Engineer

OR · On-site +1

$147K - $178K/yr

Partner with product engineering to establish data contracts and schema standards around event telemetry, ensuring data arrives in the lakehouse in a form that's reliable and ready for downstream use

... contracts, and governance. * Partner with internal teams to ensure robust data models, schemas ... Data Engineering * Data Modeling * Digital Twins * Hybrid Edge+Cloud Systems * Extract Transform ...

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Contract Data Engineering information

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 Oregon? The most popular types of Data Engineering jobs in Oregon are:
What job categories do people searching Contract Data Engineering jobs in Oregon look for? The top searched job categories for Contract Data Engineering jobs in Oregon are:
What cities in Oregon are hiring for Contract Data Engineering jobs? Cities in Oregon with the most Contract Data Engineering job openings:

Head of Data Engineering & Platform, Real-World Data (RWD)

Natera

OR • On-site

$114K - $137K/yr

Other

Posted 29 days ago


Natera rating

7.7

Company rating: 7.7 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

47th of 103 rated laboratories


Job description

Head of Data Engineering & Platform, Real-World Data (RWD)POSITION SUMMARY

Natera is seeking a leader to head Data Engineering and Platform for Real-World Data (RWD). This role will in partnership with Product drive the strategy and roadmap for the RWD platform and lead the development, operation, and delivery of data products that support clinical, research, and business priorities. The ideal candidate brings strong engineering leadership, deep technical expertise, and experience building reliable, scalable data platforms in healthcare or life sciences environments.

This leader will oversee a team focused on data engineering, data platform development, and data delivery, and will partner closely with product, bioinformatics, analytics, and AI teams to build data solutions that are useful, reliable, and easy to consume across the organization.

RESPONSIBILITIES
  • Lead, mentor, and grow a team of data engineers and SQA, with a focus on strong engineering practices, career development, and operational ownership.

  • Define and drive the strategy and roadmap for the Real-World Data platform, including capabilities that support research and analytics, rapid data mart development, and secure data de-identification and sharing.

  • Partner with product, bioinformatics, analytics, AI, software engineering, and infrastructure teams to define requirements, priorities, data contracts, and delivery models, and translate them into scalable platforms, production-grade pipelines, and reusable data products for clinical, molecular, genomic, and real-world data.

  • Lead the delivery of curated datasets, data marts, and consumer-facing data solutions, defining data SLAs and service expectations to ensure products are reliable, timely, well-documented, and fit for downstream use.

  • Provide technical leadership across data platform architecture, system design, and engineering practices, including data quality, validation, metadata, lineage, observability, testing, and operational support.

  • Drive execution across the team through planning, prioritization, estimation, hiring, and delivery management, while balancing long-term platform investments with near-term business needs.

QUALIFICATIONS
  • Bachelor's, Master's or PhD degree in Computer Science, Engineering, Bioinformatics, or a related technical field; advanced degree is a plus.

  • 8+ years of experience in software engineering or data engineering, including substantial experience building production-grade data platforms, pipelines, and data products, along with 4+ years of engineering leadership experience.

  • Strong hands-on expertise in Python, SQL, and modern data engineering practices, including pipeline development, data modeling, workflow orchestration, testing, code reviews, and agile delivery.

  • Deep experience designing and operating scalable, secure, and observable data platforms in cloud environments, with AWS strongly preferred.

  • Experience with modern data warehouse and query technologies such as Snowflake, Redshift, PostgreSQL, Athena, or similar platforms, along with strong knowledge of relational and analytical data systems.

  • Experience working with healthcare, clinical, genomic, or real-world data domains, including environments requiring strong governance, de-identification, and secure handling of sensitive data.

  • Experience building and operating data platforms with strong DevOps and operational practices, including CI/CD, observability, infrastructure automation, production support, and secure access patterns.

  • Proven ability to lead and develop strong teams while remaining technically credible, with strong communication, collaboration, and execution skills.

  • Experience partnering with research, bioinformatics, scientific, or analytical users to understand workflow needs and deliver effective data products and platform capabilities is strongly preferred.

  • Hands-on experience with bioinformatics pipelines, molecular and clinical data, and healthcare data models such as FHIR or OMOP is strongly preferred.

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