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Data Engineer Sports Analytics Jobs in Austin, TX

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

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Work cross-functionally with engineers, analysts, and stakeholders to understand requirements and deliver data solutions that support sprint-based delivery. * Support pod-level delivery by producing ...

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Your role will entail close collaboration with data scientists, analysts, and product teams to ... Engineering, or a related) Preferred Qualifications Three or more years of experience in software ...

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

You will partner closely with engineers, technical leads, analysts, and business stakeholders to design, build, and optimize data pipelines that deliver trusted, actionable insights across the ...

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Develop and implement tools, scripts, queries or applications for accessing, analyzing, converting and migrating data between databases or from csv files to databases * Reverse engineer data models ...

Data Engineer

Austin, TX · On-site +1

$113K - $136K/yr

Develop and implement tools, scripts, queries or applications for accessing, analyzing, converting and migrating data between databases or from csv files to databases * Reverse engineer data models ...

Data Engineer

Austin, TX

$137K - $250K/yr

Your role will entail close collaboration with data scientists, analysts, and product teams to ... programming language Experience with Oracle SQL and database design principles Experience with ...

Data Engineer

Austin, TX · On-site +1

$113K - $136K/yr

Data Engineer Remote At IPT Associates (IPTA), we enjoy solving real-world problems with technology ... Help structure data so it can support visualization, analysis, reporting, and AI-assisted workflows ...

Data Engineer

Austin, TX

$137K - $250K/yr

Your role will entail close collaboration with data scientists, analysts, and product teams to ... programming language Experience with Oracle SQL and database design principles Experience with ...

Data Engineer

Austin, TX

$137K - $250K/yr

Your role will entail close collaboration with data scientists, analysts, and product teams to ... programming language Experience with Oracle SQL and database design principles Experience with ...

Databricks Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Build and optimize data warehouses, data marts, and analytical solutions. * Implement data ... Mentor data engineers, analysts, and architects on Databricks technologies and platform adoption.

New

Customer Engineer, Data & Analytics

Austin, TX · On-site

$113K - $136K/yr

As a Customer Engineer, Data & Analytics, you will be the technical expert in client-facing roles, focusing on designing and delivering data solutions on Google Cloud Platform, while collaborating ...

Data Engineer

Austin, TX · Remote

$113K - $136K/yr

Partner with engineers, analysts, and business teams to develop scalable data warehouse and ... lakehouse solutions * Integrate data from internal and third-party systems using APIs, FTP/SFTP ...

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Showing results 1-20

Data Engineer Sports Analytics information

See Austin, TX salary details

$44.1K

$128.6K

$175.9K

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

As of Aug 23, 2026, the average yearly pay for data engineer sports analytics in Austin, TX is $128,576.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

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 Austin, TX?

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

What job categories do people searching Data Engineer Sports Analytics jobs in Austin, TX look for?

The top searched job categories for Data Engineer Sports Analytics jobs in Austin, TX are:

What cities near Austin, TX are hiring for Data Engineer Sports Analytics jobs?

Cities near Austin, TX with the most Data Engineer Sports Analytics job openings:

Infographic showing various Data Engineer Sports Analytics job openings in Austin, TX as of June 2026, with employment types broken down into 97% Full Time, and 3% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $128,576 per year, or $61.8 per hour.

Data Engineer / Analytics Engineer - People Analytics

RXinsider LTD.

Austin, TX • On-site

$110 - $160/hr

Other

Posted 5 days ago


Job description

Why Join Omnicell?

At Omnicell, we’re transforming how healthcare organizations operate—starting with our people. The People Analytics team is evolving beyond traditional dashboards to build a trusted, scalable data foundation that powers insight, compliance, and innovation across the enterprise.

As a Data Engineer / Analytics Engineer – People Analytics, you’ll play a critical role in designing and building the People Data Hub that enables trusted HR reporting today and prepares Omnicell for Workday, AI‑enabled analytics, and future HR system integrations. This is a high‑impact role for an engineer who enjoys building durable data platforms, reducing operational risk, and enabling analytics at scale.

What You’ll Do

Purpose: Build and maintain the core data foundation that enables secure, governed, and scalable People analytics across Omnicell.

As a Data Engineer / Analytics Engineer, You Will:Data Engineering & Ingestion
  • Design, build, and maintain automated ingestion pipelines from HR and People systems using APIs, databases, and file‑based sources
  • Ingest and transform data using modern platforms such as Microsoft Fabric, Databricks, and SQL‑based environments
  • Monitor data pipelines and proactively resolve refresh failures, schema changes, and upstream data quality issues
  • Implement reusable, scalable transformation patterns that minimize report‑level logic and improve long‑term reliability
Analytics Engineering & Data Modeling
  • Build and maintain analytics‑ready data models (facts, dimensions, and semantic layers) aligned to defined standards
  • Centralize metric definitions and business logic to ensure consistent, trusted reporting across the organization
  • Create, manage, and optimize certified Power BI datasets for reuse by Reporting Analysts and business partners
  • Optimize models for performance, scalability, and downstream analytics consumption
Power BI Enablement (Scoped)
  • Support Power BI primarily at the dataset and data‑model level, not pixel‑level report design
  • Define standardized measures and KPI logic to enable governed self‑service analytics
  • Build or refine foundational dashboards when needed to validate data models or support adoption
Collaboration & Governance
  • Partner closely with the People Analytics Lead on architecture, standards, and prioritization
  • Enable Reporting Analysts with clean, reliable, and well‑documented datasets
  • Align data engineering work with HRIS, IT, and Workday readiness initiatives, ensuring security, privacy, and scalability
Who You AreMinimum Qualifications
  • Minimum 3 years of experience building and supporting production‑grade data pipelines and transformations
  • Strong SQL expertise and experience working with relational and analytical data models
  • Hands‑on experience with Databricks, including ingestion, transformations, notebooks, and Delta Lake concepts
  • Experience working in modern data platforms such as Microsoft Fabric, data lakes, or cloud analytics environments
  • Proven ability to design analytics‑ready data models (facts, dimensions, semantic layers)
  • Experience supporting Power BI through dataset development, measure definition, and performance optimization
  • Experience working with sensitive or regulated data (HR, financial, or similar), including role‑based access and privacy controls
  • Strong documentation skills for data models, pipelines, and assumptions
Preferred Qualifications
  • Experience working with HR, People, or workforce data domains
  • Exposure to REST API‑based integrations (e.g., Workday, Oracle, or similar systems)
  • Familiarity with AI‑enabled analytics concepts (e.g., natural‑language querying or Copilot‑style tools), without direct model development responsibility
How You’ll Elevate At Omnicell

At Omnicell, success isn’t just about what you build—it’s about how you build it. Our Elevate Behaviors define how we work and grow together.

As a Data Engineer / Analytics Engineer, You Will:
  • Collaborate by partnering with People Analytics, HRIS, IT, and Reporting Analysts to deliver reusable, trusted data assets
  • Inspire confidence in People data by engineering reliable pipelines and consistent metrics that leaders can trust
  • Develop by continuously improving data models, platform patterns, and documentation that scale beyond individual ownership
  • Execute with discipline—monitoring pipelines, resolving issues quickly, and delivering durable solutions
  • Impact the organization by enabling governed analytics today and laying the groundwork for AI‑enabled insights tomorrow
Role Scope & GuardrailsThis Role Is not Responsible For:
  • Data science or machine learning model development
  • Predictive analytics ownership
  • Ongoing ad‑hoc dashboard requests or executive storytelling
  • Pixel‑level Power BI report design
Focus:

Build once. Reuse everywhere. Engineer for trust today—enable intelligence tomorrow.

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