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Data Engineer Sports Analytics Jobs in West Virginia

Lead Data Engineer

WV · On-site +1

$103K - $123K/yr

Data Analysis, Data Analytics, Data Lake, Data Warehousing (DW) Certifications: None Experience: 7 + years of related experience US Citizenship Required: No Lead Data Engineer Seize your opportunity ...

Data Engineer

Charleston, WV · Remote

$106K - $127K/yr

You will partner closely with the BI & Analytics Developer(s) and business stakeholders to ensure the underlying data is accurate, well-governed, and structured to support self-service reporting and ...

$94K - $113K/yr

Partner with Data Scientists, Business Analysts, and Sustainability Specialists to deliver clean ... Core Programming: Strong foundation in Python and fundamental software engineering principles (OOP ...

Data Engineer Staff

Charleston, WV · On-site

$106K - $127K/yr

Lead large-scale, high-impact initiatives ranging from serving broad, historic analytics data to ... Engineer every stage to be idempotent and atomic - safe to retry or replay without duplication ...

Sr. Data Engineer

Charleston, WV · On-site +1

$106K - $127K/yr

Data Engineer for a full-time role based in Austin, TX, Nashville, TN, or remote. Our development ... and analyze large-scale data solutions. * Translate complex business requirements into clear ...

Data Engineer, Security

WV · On-site +1

$163K/yr

... analytics . * Pipeline Engineering: Build scalable ELT pipelines using Snowflake and dbt, ensuring ... Implement data masking, RBAC, and secure data handling practices . * Engineering Excellence ...

Data Engineer (Remote)

Glen Dale, WV · Remote

$96K - $116K/yr

Analyze and convert unstructured, document-heavy data into structured, analytics-ready formats ... engineering, data migration, or data integration roles * Proven experience executing large-scale ...

Analytics Engineer

WV · On-site +1

$127K - $172K/yr

Data Science and Data Engineering Job Qualifications: Skills: Data Modeling, GitLab CI/CD ... Yes The Senior Analytics Engineer provides advanced analytics and data engineering support across ...

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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 West Virginia?

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

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

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

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

Cities in West Virginia with the most Data Engineer Sports Analytics job openings:

Data Engineer - Clearance Required with Security Clearance

LMI

True, WV • On-site

$101K - $170K/yr

Contractor

Re-posted 7 days ago


Key responsibilities

  • Design, develop, and maintain data ingestion and transformation pipelines supporting H2FMS analytics and research use cases.

  • Integrate data from multiple sources and ensure pipelines are reliable, scalable, and support downstream analytic and reporting needs.

  • Support data access, validation, troubleshooting, and documentation to enable data preparation for analytics, research, and modeling activities.


Job description

Overview LMI seeks an experienced Data Engineer to support the U.S. Army's Holistic Health & Fitness (H2F) initiative as a member of the Analytics functional team within the H2F Program Support Team. The Data Engineer is responsible for designing, building, and maintaining data pipelines and data services that enable scientific analysis, analytics, and user engagement activities within the Holistic Health and Fitness Management System (H2FMS). This role focuses on data ingestion, transformation, storage, and accessibility, ensuring that data supporting research, analytics, and decision support is reliable, well-structured, and available for authorized use. The Data Engineer works closely with the Technical Project Manager, data governance specialists, epidemiologists, research psychologists, tactical sports scientists, data scientists, and software teams to translate analytic and research requirements into scalable data solutions under Government direction. This role does not set independent data policy or analytic strategy. LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed. Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors-helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value. Responsibilities * Design, develop, and maintain data ingestion and transformation pipelines supporting H2FMS analytics and research use cases. * Integrate data from multiple sources, including surveys, wearable and performance data, health and injury datasets, and operational systems as directed. * Ensure pipelines are reliable, scalable, and support downstream analytic and reporting needs. * Support development of analytic data models optimized for reporting, dashboards, and advanced analytics. * Work with data governance staff to ensure data models align with approved data definitions and standards. * Assist with management of structured and semi-structured data stores used within H2FMS. * Enable data access and preparation for data scientists and AI/ML engineers, ensuring data is usable for modeling and analysis. * Support feature preparation and data validation activities under Government and senior analytic direction. * Assist in troubleshooting data-related issues impacting analytics or models. * Support monitoring and resolution of data quality issues, including completeness, consistency, and timeliness. * Implement basic validation, logging, and error-handling mechanisms within data pipelines. * Coordinate with data governance and analytics teams to address recurring data issues. * Collaborate with epidemiologists, research psychologists, and tactical sports scientists to understand analytic data needs. * Coordinate with software teams to support integration between data services and application components. * Support documentation and communication of data pipeline designs and dependencies. Qualifications Required Qualifications * Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field. * Demonstrated experience building and maintaining data pipelines and data integration solutions. * Familiarity with data transformation, storage, and analytics enablement concepts. * Experience working with structured and semi-structured data. * Ability to collaborate effectively within multidisciplinary teams spanning analytics, research, and software. * Strong problem-solving and communication skills. * Ability to obtain and maintain a Secret security clearance. Desired Qualifications * Experience supporting analytics or research-driven data environments. * Familiarity with cloud-based data services or analytics platforms. * Experience preparing data for dashboards, reporting, or AI/ML workflows. * Prior experience supporting DoW or federal customers. Location & Travel * Duty Location: This position may be performed in a remote or hybrid capacity. * Travel: Limited travel to Fort Eustis, Virginia or LMI Headquarters may be required to support planning, integration, or stakeholder engagement. Target salary range: $101,986 - $170,154 The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances. Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work. Job Locations US-Remote