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Data Engineer Sports Analytics Jobs in Washington

Platinum Technologies

Data Engineer

Herndon, VA · On-site

$117K - $141K/yr

The Data Engineering Subject Matter Expert serves as the senior technical authority for developing ... Collaborate with ontology engineers, software engineers, database engineers, analysts, and ...

Platinum Technologies

Data Engineer

Herndon, VA

$117K - $141K/yr

The Data Engineering Subject Matter Expert serves as the senior technical authority for developing ... Collaborate with ontology engineers, software engineers, database engineers, analysts, and ...

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

GRVTY

Data Engineer

Chantilly, VA

$117K - $140K/yr

The Data Engineer will work with and analyze our client's challenges and provide solutions by designing and implementing batch and streaming data pipelines. What You Must Have * Active TS/SCI with ...

Accenture Federal Services

Data Engineer

Washington, DC

$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

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 ...

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 ...

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 ...

Peraton

Data Engineer - Analytics Platforms

Herndon, VA

$117K - $141K/yr

Minimum of a BS degree with 5+ years of experience, MS degree with 3+ YoE, or PhD in Computer Science, Data Engineering, Information Systems, Data Analytics, or a related field * Strong hands-on ...

Peraton

Data Engineer - Analytics Platforms

Herndon, VA · On-site

$86 - $138/hr

Minimum of a BS degree with 5+ years of experience, MS degree with 3+ YoE, or PhD in Computer Science, Data Engineering, Information Systems, Data Analytics, or a related field * Strong hands‑on ...

Hatch IT

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

The Data Engineer will work as part of a multidisciplinary team integrating data engineering, advanced analytics, machine learning, and software engineering capabilities into mission-critical ...

Hatch IT

Data Engineer

Washington, DC

$129K - $155K/yr

The Data Engineer will work as part of a multidisciplinary team integrating data engineering, advanced analytics, machine learning, and software engineering capabilities into mission-critical ...

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Showing results 21-40

All JobsData Engineer Sports Analytics JobsData Engineer Sports Analytics Jobs in Washington

Data Engineer Sports Analytics information

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.

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 are popular job titles related to Data Engineer Sports Analytics jobs in Washington?

For Data Engineer Sports Analytics jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Data Engineer Sports Analytics jobs in Washington look for?

The top searched job categories for Data Engineer Sports Analytics jobs in Washington are:

What cities in Washington are hiring for Data Engineer Sports Analytics jobs?

Cities in Washington 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 Washington 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.

Data Engineer

Platinum Technologies

Herndon, VA • On-site

$117K - $141K/yr

Full-time

Posted 12 days ago

Job description

Who we are.
Platinum Technologies is a Northern Virginia based integrated solutions firm that specializes in Cybersecurity, Cloud and Digital Services to the Public Sector. Our team solves hard problems and helps our Mission Partners achieve their goals. If you are self-motivated, possess demonstrated learning agility, and are passionate about delivering high-quality work products - we want to hear from you.
We lead with technical expertise, but that is just the tip of the iceberg - the 'Why' matters. At Platinum, we don't hire people to do a job. We provide professional and leadership development to complement our self-motivated domain experts. Our teammates are dot-connecting leaders that operate in a mutually accountable environment to deliver thought leadership, expert technical analysis, and quality execution for our clients.
This position requires an active U.S. Government Security Clearance at the TS/SCI level with CI polygraph.
You.
Platinum Technologies is seeking a Data Engineering Subject Matter Expert (SME) to join our team. In this position you will provide technical leadership for the design, implementation, and optimization of enterprise data engineering solutions supporting Object-Based Intelligence (OBI) mission requirements, ontology-driven data integration, and advanced analytics.
The Data Engineering Subject Matter Expert serves as the senior technical authority for developing and implementing scalable data architectures, pipelines, and integration frameworks that enable the ingestion, transformation, management, and delivery of structured, semi-structured, and unstructured data. This position applies data engineering best practices to support enterprise ontologies, knowledge graphs, Semantic Web technologies, and AI/ML applications while ensuring data quality, governance, interoperability, and security across diverse mission systems. Working closely with ontology engineers, software engineers, database engineers, data scientists, and Government stakeholders, the Data Engineering SME develops modern data solutions that support mission analytics, knowledge discovery, and decision advantage.
What you get to do.
  • Lead the design, development, and implementation of enterprise data engineering solutions supporting Object-Based Intelligence mission requirements.
  • Design and optimize scalable data pipelines for ingesting, transforming, validating, and integrating data from multiple internal and external sources.
  • Develop data integration frameworks that support enterprise ontologies, knowledge graphs, and Semantic Web technologies, including RDF, OWL, and SPARQL.
  • Collaborate with ontology engineers, software engineers, database engineers, analysts, and Government stakeholders to translate mission requirements into scalable data engineering solutions.
  • Design and implement data architectures supporting cloud-native, distributed, and hybrid computing environments.
  • Establish data quality, metadata management, lineage, and governance processes to ensure consistency, traceability, and interoperability across enterprise data assets.
  • Optimize data processing performance using modern distributed processing frameworks and scalable storage technologies.
  • Support AI/ML initiatives by developing reliable, high-quality data pipelines that provide curated datasets and semantic context for model training, inference, and decision support.
  • Develop automated monitoring, validation, and testing capabilities to ensure data accuracy, completeness, and operational reliability.
  • Produce and maintain technical documentation, data flow diagrams, interface specifications, data dictionaries, and engineering standards.
  • Provide technical leadership, mentoring, and knowledge transfer activities to Government personnel and project team members regarding data engineering best practices, modern data architectures, and enterprise integration strategies.

Required Skills.
  • Must be a U.S. citizen and have an active TS/SCI with CI polygraph.
  • Minimum twelve (12) years of experience and an advanced degree or 17 years of experience with a bachelor's degree.
  • Demonstrated experience designing and implementing enterprise-scale data engineering solutions and data integration architectures.
  • Experience developing ETL/ELT pipelines using modern data engineering tools and frameworks.
  • Experience integrating structured, semi-structured, and unstructured data from heterogeneous enterprise data sources.
  • Experience with relational databases, NoSQL databases, graph databases, and distributed data processing platforms.
  • Knowledge of data modeling, metadata management, data governance, and enterprise data architecture principles.
  • Familiarity with Semantic Web technologies, knowledge graphs, or ontology-based data integration.
  • Experience supporting cloud-based or containerized data platforms, including Kubernetes and OpenShift.
  • Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.

The Company is an Equal Opportunity/Affirmative Action employer. All qualified candidates will receive consideration for employment without regard to disability, protected veteran status, race, color, religious creed, national origin, citizenship, marital status, sex, sexual orientation/gender identity, age, or genetic information.
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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