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Data Engineer Sports Analytics Jobs in Oregon (NOW HIRING)

Versapay

OR

$105K - $143K/yr

The Analytics team is evolving our enterprise capabilities from foundational governance into a ... As a Senior Data Engineer, you will be pivotal in optimizing and scaling our foundational Snowflake ...

Wellbe Senior Medical

Senior Data Engineer

$105K - $150K/yr

SKILLS & COMPETENCIES Coach and mentor the Analytics Engineering team: guiding, planning, and reviewing the team's work. Collaborate with senior management to define and execute the company's data ...

Origami Risk LLC

Senior Data Engineer

$117K - $146K/yr

Overview The Senior Data Engineer plays a pivotal role within our expanding Data and AI team. This ... Collaborates with analytics teams to ensure data availability and quality for reporting and machine ...

Imagine Pediatrics

OR · On-site

$150K - $180K/yr

This role requires a mix of technical expertise and analytical thinking, applying engineering best practices to transform raw data from a variety of sources into well-defined, consumable datasets and ...

Origami Risk LLC

Senior Data Engineer

$117K - $146K/yr

Overview The Senior Data Engineer plays a pivotal role within our expanding Data and AI team. This ... Collaborates with analytics teams to ensure data availability and quality for reporting and machine ...

Netflix

OR · On-site

$380K - $610K/yr

We are looking for passionale, mature, and curious software engineers with strong data intuition, analytical mindset and ad ecosystem experience, to contribute to the team's impact in a quickly ...

Sonny's Enterprises LLC

$105K - $143K/yr

The Senior Data Engineer is the lead delivery role for structured data engineering in Databricks ... analytics and AI. Implement data quality checks, reconciliation logic, documentation, and ...

Cotiviti

Data Engineer - AI

$101K - $132K/yr

Perform data analysis and identify any issues. * Work with other groups such as Engineering team, DBA, Cloud ops, etc. to troubleshoot and resolve any environmental or network issues that impact your ...

Roseburg

BI Data Engineer

Springfield, OR · On-site

Purpose The BI (Business Intelligence) Data Engineer will be responsible for designing ... Design, develop, test, and deploy Business Intelligence analytics and reporting solutions * Lead ...

Human Interest

OR

$105K - $143K/yr

Mentor data engineers and analysts, raising the technical bar across the team. What you bring to the role * 5+ years of experience as a Data Engineer with a strong focus on production data pipelines ...

Moda Health

Data Engineer I, II

Portland, OR · On-site +1

$78K - $110K/yr

Demonstrated analytical skills and ability to contribute to data driven solutions that address real business problems, with guidance from senior engineers when needed. * Working knowledge of Agile ...

Pwc

Data Engineer - Senior Associate

Portland, OR · On-site

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Sonny's Enterprises LLC

$114K - $137K/yr

Qualifications 5+ years of experience in machine learning engineering, data engineering, analytics engineering, applied AI engineering, or production forecasting. Strong hands-on experience with ...

Roseburg Forest Products

BI Data Engineer

Springfield, OR · On-site +1

$52.75 - $68.50/hr

Design, develop, test, and deploy Business Intelligence analytics and reporting solutions * Lead ... engineering and the effective application of generative AI capabilities within D360 to support data ...

Cotiviti

Principal Data Engineer AI

Principal Data Engineers establish the data foundation of Cotiviti's clinical AI platform-the ... Own the data quality framework-the validation, evaluation, and analysis pipelines that measure ...

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All JobsData Engineer Sports Analytics JobsData Engineer Sports Analytics Jobs in Oregon

Data Engineer Sports Analytics information

How does a data engineer in sports analytics typically collaborate with data scientists and analysts on a project?

As a Data Engineer in Sports Analytics, you’ll regularly work alongside data scientists and analysts to ensure high-quality, reliable data is available for modeling and analysis. Your responsibilities often include building and maintaining data pipelines, transforming raw sports data into usable formats, and optimizing data storage for performance. Effective communication is key, as you’ll need to understand the analytical requirements and adjust pipelines or data sources accordingly. Collaboration often happens through regular meetings, shared documentation, and close feedback loops to align on project goals and data needs.

What is the difference between Data Engineer Sports Analytics vs Data Analyst Sports Analytics?

AspectData Engineer Sports AnalyticsData Analyst Sports Analytics
Primary FocusBuilding and maintaining data pipelines, infrastructure, and databasesAnalyzing data, generating reports, and providing insights
Skills & CertificationsSQL, Python, data warehousing, cloud platformsExcel, SQL, statistical analysis, visualization tools
Work EnvironmentData engineering teams, IT infrastructureBusiness teams, sports analytics departments
Industry UsageSports organizations, tech companies supporting sports dataSports teams, media outlets, betting companies

While Data Engineer Sports Analytics focuses on building and maintaining the data infrastructure necessary for sports data analysis, Data Analyst Sports Analytics concentrates on interpreting that data to generate actionable insights. Both roles are essential in sports analytics but serve different functions within the data ecosystem.

What does a data engineer in sports analytics do?

A Data Engineer in Sports Analytics designs, builds, and maintains the infrastructure and systems that collect, store, and process large volumes of sports-related data. They ensure data pipelines are efficient and reliable so that analysts and data scientists can access accurate information for player performance analysis, game strategy, and business decisions. Their work involves integrating data from various sources, optimizing databases, and implementing best practices in data security and quality, all within the context of the sports industry.

What are the key skills and qualifications needed to thrive as a data engineer in sports analytics?

To thrive as a Data Engineer in Sports Analytics, you need a strong background in computer science, data modeling, and database management, typically supported by a relevant degree and experience with large data sets. Familiarity with tools and technologies such as SQL, Python, Spark, cloud platforms (AWS, Azure), and ETL pipelines is essential, and certifications in these areas can be advantageous. Excellent problem-solving, teamwork, and communication skills help you collaborate with analysts, coaches, and stakeholders to translate data into actionable insights. These competencies ensure the efficient collection, processing, and delivery of high-quality sports data that drive performance analysis and competitive advantage.
What are popular job titles related to Data Engineer Sports Analytics jobs in Oregon? For Data Engineer Sports Analytics jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Data Engineer Sports Analytics jobs in Oregon look for? The top searched job categories for Data Engineer Sports Analytics jobs in Oregon are:
What cities in Oregon are hiring for Data Engineer Sports Analytics jobs? Cities in Oregon with the most Data Engineer Sports Analytics job openings:
Data Engineer Sports Analytics jobs near you
Infographic showing various Data Engineer Sports Analytics job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Data Engineer

Versapay

OR

$105K - $143K/yr

Full-time

Re-posted 20 days ago

Job description

About Versapay 

Versapay turns accounts receivable (AR) into a competitive advantage.

Inefficient AR processes slow cash flow and stall growth. Versapay removes friction, unlocks working capital, and accelerates momentum - giving finance leaders the clarity and control they need to drive business forward.

Versapay automates accounts receivable, removing barriers to collecting and reconciling B2B payments. Our solutions connect finance teams, customers, and business systems in one ecosystem to ensure cash flow clarity. With over 10,000 customers and 5M+ companies transacting on the platform, Versapay processes over 110M transactions and $257B annually.

Think you might be the next Veep to join? Read on!!




Here's how you'll make a huge impact here - and on your career: 

The Analytics team is evolving our enterprise capabilities from foundational governance into a robust data platform, safely accelerating strategic AI enablement and delivering high-margin commercial data products. As a Senior Data Engineer, you will be pivotal in optimizing and scaling our foundational Snowflake architecture while aggressively pushing toward agentic engineering and machine learning operations. You will operate as a full-stack generalist within the engineering pod, sharing cross-functional responsibility for pipeline resilience, advanced observability, and the deployment of intelligent semantic models that directly feed our product ecosystem. 

Reports To: Manager of Data Engineering 

 
What You'll Do:

  • Architect for the Future: Optimize our existing Snowflake architecture, establishing strict environmental isolation and scalable structures that prepare our data for eventual downstream commercialization and product offerings. 

  • Drive Agentic Engineering: Leverage tools like Snowflake Cortex, Cursor, and UiPath to automate workflows, build semantic models, and deploy agents that accelerate time-to-value. 

  • Establish Data Observability: Implement and manage robust data quality and observability frameworks to ensure pipeline reliability and proactive issue resolution. 

  • Operationalize Machine Learning: Design and maintain MLOps pipelines to support the seamless rollout, monitoring, and lifecycle management of ML models directly within Snowflake. 

  • Execute Shared Ownership: Partner closely with your peers under the Data Engineering Manager to share responsibilities across pipeline management, MLOps, and architecture, avoiding siloed knowledge and ensuring comprehensive team coverage. 

  • Model for Enterprise Utility: Synthesize disparate operational entities into a unified, enterprise-wide semantic model that supports both internal analytics and future data monetization efforts. 

Qualifications

  • 5+ years of Data Engineering experience with a deep, specialized focus on Snowflake's advanced features (e.g., RBAC, materialized views, dynamic tables, Snowpipe, stored procedures). 

  • Advanced proficiency in SQL and Python, with a strong foundation in applying software engineering best practices to ELT processes. 

  • Observability Expertise: Hands-on experience implementing data observability and monitoring platforms (such as DataDog) to manage data quality at scale. 

  • AI & MLOps Exposure: Demonstrated experience using AI-assisted development tools (e.g., Cursor, Cortex) and familiarity with MLOps principles for productionalizing machine learning models. 

  • Pipeline Management: Experience building and maintaining resilient, low-touch data pipelines using modern integration and orchestration tools (e.g., Fivetran, AWS Glue, AWS Lambda). 

What You'll Bring To The Team:
  • Technical Competency: Advanced SQL skills, proficiency with Python/R, and experience with BI tools. Focus on self-sufficiency and leveraging AI tools to accelerate development. 
  • "Builder" Mentality: An ability to thrive in fast-paced environments with a track record of defining and executing high-impact initiatives. A desire to solve complex problems, remediate technical debt, and find creative solutions for scaling our platform. 
  • Business Acumen: Strong business acumen with a proven ability to translate complex data analysis into strategic recommendations. Adept at identifying key drivers and influencing decision-making. You understand the business behind the data and the path to commercialization. 
  • Empathetic Collaboration: Assertive with humility - able to communicate both persuasively and positively. Maintain high standards for verbal and written communication while seamlessly sharing domain responsibilities across the engineering pod. 
  • Trusted Advisor: Possesses a high degree of integrity, the relentless pursuit of truth, and an ability to inspire change, particularly in championing data quality and observability standards. 
What Will Make You Stand Out:

  • Deep domain expertise navigating complex merchant payment ecosystems (e.g., Adyen), operating under rigorous enterprise data governance and security standards. 

  • Proven ability to architect the translation of high-velocity transactional events into highly optimized, columnar analytical architectures. 

  • Direct experience architecting data products for commercialization, external endpoints, or embedded analytics within a SaaS platform.

$110,000 - $140,000 a year
#LI-Remote

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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