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Data Engineer Sports Analytics Jobs in Reston, VA

Pantheon Data

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Collaborate with analysts, data scientists, and stakeholders. Required Skills and Experience * Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field. * AWS ...

Pantheon Data

Data Engineer

Washington, DC · On-site

$80K - $120K/yr

Collaborate with analysts, data scientists, and stakeholders. Required Skills and Experience * Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field. * AWS ...

Meta

Data Engineer, Product Analytics

Washington, DC · On-site +1

$147K/yr

Data Engineer, Product Analytics Responsibilities: * Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs ...

Elder Research

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

Data Engineer General Information Requisition # 675 Locations USA-VA-Arlington Posting Date 03/04 ... This role sits within an analytics-focused business unit supporting IRS enforcement, compliance ...

Elder Research

Data Engineer

Arlington, VA

$131K - $158K/yr

Data Engineer General Information Requisition # 675 Locations USA-VA-Arlington Posting Date 03/04 ... This role sits within an analytics-focused business unit supporting IRS enforcement, compliance ...

AaraTechnologies Inc

DATA ENGINEER

Washington, DC · On-site

$129K - $155K/yr

Data Engineer Retail & E-Commerce (2-3 Years Experience) Company: AaraTech Inc About the Role ... You will collaborate with analytics teams to support reporting needs. Ideal for early-career data ...

AaraTechnologies Inc

DATA ENGINEER

Washington, DC · On-site

$129K - $155K/yr

Data Engineer Retail & E-Commerce (2-3 Years Experience) Company: AaraTech Inc About the Role ... You will collaborate with analytics teams to support reporting needs. Ideal for early-career data ...

ProSidian Consulting

Data Engineer

Alexandria, VA · Hybrid

$122K - $147K/yr

We seek Data Engineer | Workforce Planning & Strategic Human Capital Analytics - Training Analytics & Optimization [NSF0038038] candidates with relevant Government And Public Services Sector ...

Accenture Federal Services

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

Develop efficient data processing and transformation workflows to support analytics and reporting ... Experience with COTS and open-source data engineering tools such as ElasticSearch and NiFi

eSolutionsFirst, LLC

Data Engineer

Mclean, VA · On-site

$117K - $141K/yr

This role will collaborate closely with data analysts, software engineers, architects, and business stakeholders to deliver reliable, high-quality data solutions. Key Responsibilities * Design ...

IT America Inc

Data Engineer

Mclean, VA · On-site

$115K - $139K/yr

Data Engineer Location: Mclean, VA Duration: Long term contract Note: Looking for Ex-Capital One ... This role involves working closely with Capital One's data, analytics, and technology teams to ...

Booz Allen Hamilton

Data Engineer

Arlington, VA · On-site

$62K - $141K/yr

As a data engineer, you know that organizing data can yield pivotal insights when it's gathered ... You'll sharpen your skills in analytical exploration and data examination while you support the ...

Booz Allen Hamilton, Inc.

Data Engineer

Arlington, VA · On-site +1

$62K - $141K/yr

Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and ... You'll sharpen your skills in analytical exploration and data examination while you support the ...

Booz Allen Hamilton

Data Engineer

Arlington, VA

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... You'll sharpen your skills in analytical exploration and data examination while you support the ...

KDA Consulting Inc

Data Engineer

Mclean, VA · On-site

$115K - $139K/yr

This role focuses on enabling efficient data processing, analytics, and decision-making by ... Data Pipeline Development & Engineering * Design, develop, and maintain scalable ETL/ELT pipelines ...

Altus Consulting Corp

Data Engineer

Herndon, VA · On-site

$117K - $141K/yr

Collaborate with data scientists and analysts to understand their needs and deliver data that meets ... Strong programming skills (Python, Java, Scala). * Experience with Big Data technologies (Hadoop ...

KDA Consulting Inc

Data Engineer

Chantilly, VA · On-site

$117K - $140K/yr

This role focuses on enabling efficient data processing, analytics, and decision-making by ... Data Pipeline Development & Engineering * Design, develop, and maintain scalable ETL/ELT pipelines ...

Altus Consulting Corp

Data Engineer

Herndon, VA · On-site

$117K - $141K/yr

Collaborate with data scientists and analysts to understand their needs and deliver data that meets ... Strong programming skills (Python, Java, Scala). * Experience with Big Data technologies (Hadoop ...

Altus Consulting Corp

Data Engineer

Herndon, VA

$117K - $141K/yr

Collaborate with data scientists and analysts to understand their needs and deliver data that meets ... Strong programming skills (Python, Java, Scala). * Experience with Big Data technologies (Hadoop ...

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All JobsData Engineer Sports Analytics JobsData Engineer Sports Analytics Jobs in Reston, VA

Data Engineer Sports Analytics information

See Reston, VA salary details

$46.3K

$135K

$184.7K

How much do data engineer sports analytics jobs pay per year?

As of Jul 17, 2026, the average yearly pay for data engineer sports analytics in Reston, VA is $134,951.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $143,000.00 per year, depending on experience, location, and employer.

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.

How much do NFL data analysts make?

NFL data analysts typically earn between $60,000 and $100,000 annually, depending on experience, education, and the level of responsibility. These roles often require proficiency in data analysis tools, programming languages, and sports analytics knowledge. Salaries can vary based on the organization and geographic location.

Can a data analyst work in sports?

A data analyst can work in sports by analyzing player performance, game statistics, and team data to support decision-making. Skills in data visualization, statistical analysis, and tools like SQL and Python are commonly used in sports analytics roles. Transitioning to sports analytics often requires knowledge of the sport and relevant data sources.

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, and why are they important?

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.

Do NFL teams hire data analysts?

Yes, NFL teams often hire data analysts and data engineers to analyze player performance, game strategies, and injury data. These roles typically require skills in data management, statistical analysis, and familiarity with sports analytics tools like R or Python. Data professionals help teams make data-driven decisions to improve performance and competitiveness.

Is 40 too late for data science?

For a Data Engineer in sports analytics, starting a career at 40 is feasible, especially with relevant skills in programming, data management, and analytics tools. Many professionals transition into data roles later in life, and experience in related fields can be an advantage. Continuous learning and certifications can help accelerate entry into the field regardless of age.
What are popular job titles related to Data Engineer Sports Analytics jobs in Reston, VA? For Data Engineer Sports Analytics jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Data Engineer Sports Analytics jobs in Reston, VA look for? The top searched job categories for Data Engineer Sports Analytics jobs in Reston, VA are:
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Data Engineer Sports Analytics jobs near you
Data Engineer (Fraud Analytics & Investigative Support)

Data Engineer (Fraud Analytics & Investigative Support)

Praescient Analytics

Fairfax, VA • On-site, Remote

$117K - $140K/yr

Full-time

Retirement, PTO

Posted 22 days ago

Job description

Location: Remote (Occasional Travel May Be Required)
Clearance: Ability to obtain and maintain a Public Trust
U.S. Citizenship is Required.
Position Overview:
Praescient Analytics is seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines supporting advanced fraud analytics and investigative solutions for a federal oversight organization. This individual will play a critical role in ensuring diverse data sources are efficiently ingested, transformed, governed, and made available for analytics, machine learning, graph analytics, and investigative support.
The ideal candidate is a hands-on engineer who enjoys solving complex data integration challenges while building modern cloud-native data pipelines that prioritize quality, reliability, scalability, and performance. They understand that high-quality analytics begin with high-quality data and are committed to developing robust data engineering solutions that enable timely, accurate, and defensible analytic products.
Key Responsibilities:
  • Design, develop, maintain, and optimize scalable ETL pipelines supporting advanced analytics and investigative workloads.
  • Ingest, transform, and integrate structured and unstructured data from diverse sources including flat files, JSON, XML, Excel, APIs, graph databases, relational databases, and other evolving data formats.
  • Develop and optimize data pipelines supporting both streaming and batch ingestion frameworks.
  • Manage, organize, and optimize data within modern cloud-based analytics platforms, including Databricks Unity Catalog, SQL Server managed instances, and Lakehouse architectures.
  • Develop efficient SQL and Python-based data transformation processes that support downstream analytics, machine learning, graph analytics, and business intelligence solutions.
  • Implement data quality validation, lineage tracking, metadata management, and monitoring processes to ensure data reliability and integrity throughout the analytics lifecycle.
  • Collaborate with Data Scientists, Graph Data Scientists, Investigative Analysts, Forensic Accountants, and Project Managers to understand data requirements and support analytic initiatives.
  • Troubleshoot pipeline failures, optimize performance, and continuously improve scalability, reliability, and maintainability of enterprise data solutions.
  • Support enterprise data governance by implementing data management standards, documenting data assets, and ensuring compliance with enterprise data management (EDM) policies.
  • Contribute to data architecture improvements, ingestion strategies, and modernization efforts that enhance overall analytic capabilities.

Required Qualifications:
  • Must have experience with Fraud Analysis
  • Three (3) or more years of professional experience in data engineering or a related technical field.
  • Demonstrated experience designing, building, maintaining, and optimizing scalable ETL pipelines across diverse data sources.
  • Strong SQL and Python programming skills, or equivalent technologies, for data ingestion, transformation, and processing.
  • Experience ingesting and transforming data from flat files, JSON, XML, Excel, APIs, graph databases, relational databases, and other structured and unstructured data sources.
  • Experience loading, managing, and optimizing data within Databricks Unity Catalog, SQL Server managed instances, or comparable cloud-based data platforms.
  • Experience working with streaming and batch ingestion frameworks and modern Lakehouse architectures.
  • Demonstrated ability to implement data quality controls, lineage tracking, reliability monitoring, and performance optimization processes.
  • Familiarity with enterprise data governance, enterprise data management (EDM), metadata management, and data quality best practices.
  • Strong analytical, problem-solving, written, and verbal communication skills.

Preferred Qualifications:
Preference will be given to candidates with demonstrated experience in one or more of the following areas:
  • Supporting fraud detection, anomaly detection, financial oversight, program integrity, or investigative analytics environments.
  • Building cloud-native data engineering solutions utilizing Azure Databricks, Azure Data Lake Storage (ADLS), Microsoft SQL Server, Microsoft Fabric, Azure Synapse Analytics, Power BI, Neo4j, Git repositories, or comparable cloud data platforms.
  • Developing scalable data pipelines supporting machine learning, artificial intelligence (AI), graph analytics, natural language processing (NLP), or advanced analytics solutions.
  • Working with public, non-public, commercial, financial, law enforcement, or cross-agency datasets supporting fraud detection and investigative missions.
  • Designing and implementing Lakehouse architectures, Delta Lake, data partitioning strategies, and performance optimization techniques for large-scale analytics environments.
  • Developing automated data quality validation, metadata management, lineage tracking, schema evolution, and monitoring capabilities.
  • Supporting enterprise data governance initiatives, data catalogs, master data management, and compliance with organizational data standards.
  • Utilizing orchestration and workflow tools such as Apache Spark, Databricks Workflows, Azure Data Factory, Airflow, or comparable pipeline automation technologies.
  • Collaborating within Agile software development teams using Git-based version control, sprint planning, backlog management, and continuous integration/continuous deployment (CI/CD) practices.
  • Supporting Offices of Inspector General (OIGs), federal oversight organizations, law enforcement agencies, or other government data modernization initiatives.

What We're Looking For:
We're looking for a data engineer who is passionate about building reliable, scalable data foundations that power advanced analytics. The ideal candidate enjoys working with complex data ecosystems, solving integration challenges, and continuously improving the quality, performance, and accessibility of enterprise data. They understand that trustworthy analytics depend on trustworthy data and take pride in developing robust engineering solutions that enable investigators and analysts to uncover fraud, waste, abuse, and emerging risks with confidence.
What you can expect from us:
  • Real opportunity for career growth in an environment where your achievements will be celebrated
  • Constant collaboration with numerous teams to ensure client success
  • A team that respects and embraces your ideas and expertise
  • Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
  • A workplace dedicated to supporting and bettering public safety and government agencies

Benefits:
  • Competitive salary based on qualifications and experience
  • Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
  • 401(k) with company match
  • Travel & performance incentives
  • 3 weeks paid time off (plus Federal Holidays)
  • $5K annual training allowance
  • $500 book allowance
  • Tuition reimbursement program

Praescient Analytics is an Equal Employment Opportunity employer. Employment decisions are based on merit, qualifications, experience, performance, business needs, and applicable contract requirements. Praescient does not unlawfully discriminate or provide disparate treatment based on race, ethnicity, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable law.
Praescient Analytics acknowledges the applicable clause and provision updates implementing Executive Order 14398, Addressing DEI Discrimination by Federal Contractors, and the related FAR/RFO updates, including FAR 52.222-90 where applicable. Praescient does not engage in racially discriminatory DEI activities, including disparate treatment based on race or ethnicity in recruitment, hiring, promotion, contracting, program participation, training, mentoring, leadership development, or allocation of company resources. Praescient's employment and contracting decisions are made based on merit, qualifications, experience, performance, business needs, and applicable contract requirements.
Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information.
US Citizenship Required
Interested Candidates: Please forward your resume to recruiting@praescientanalytics.com and please visit our website to apply online at www.praescientanalytics.applicantstack.com/x/openings.

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