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Data Engineer Sports Analytics Jobs in Indiana (NOW HIRING)

Data Engineer (AI)

Austin, IN · On-site

$135K - $155K/yr

Data Engineering is a key role in the development team and is responsible for building and ... analytics, ML training and inference, and retrieval-augmented generation (RAG) systems.

Sr Databricks Data Engineer

Indianapolis, IN

$109K - $131K/yr

Evaluate, pilot, and integrate new big data and analytics technologies, ensuring the organization remains at the cutting edge. Lead, coach, and develop teams of data engineers and architects ...

Data Engineer (in person)

Westfield, IN

$109K - $131K/yr

Implement data models for analytics use cases * Write data quality checks and tests for data ... Experience with analytics engineering tools like dbt and data catalog tools (Unity Catalog ...

Data Engineer (in person)

Westfield, IN · On-site

$109K - $131K/yr

Implement data models for analytics use cases * Write data quality checks and tests for data ... Experience with analytics engineering tools like dbt and data catalog tools (Unity Catalog ...

Data Engineer (in person)

Westfield, IN

$109K - $131K/yr

Implement data models for analytics use cases * Write data quality checks and tests for data ... Experience with analytics engineering tools like dbt and data catalog tools (Unity Catalog ...

Data Engineer - Manager

Indianapolis, IN · On-site

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary The Opportunity As a Data Engineer - Manager, you will play a pivotal role in transforming raw data ...

ETL/Data Engineer

Indianapolis, IN · On-site

$107K - $129K/yr

You will partner closely with data architects, analytics engineers, data scientists, business stakeholders, and platform engineering teams to deliver reliable, performance, secure, and costefficient ...

ETL/Data Engineer

Indianapolis, IN

$107K - $129K/yr

You will partner closely with data architects, analytics engineers, data scientists, business stakeholders, and platform engineering teams to deliver reliable, performance, secure, and costefficient ...

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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, 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.
What job categories do people searching Data Engineer Sports Analytics jobs in Indiana look for? The top searched job categories for Data Engineer Sports Analytics jobs in Indiana are:
What cities in Indiana are hiring for Data Engineer Sports Analytics jobs? Cities in Indiana with the most Data Engineer Sports Analytics job openings:
Data Engineer (AI)

Data Engineer (AI)

inKind

Austin, IN • On-site

$135K - $155K/yr

Other

Medical, Dental, Vision, PTO

Posted 18 days ago


Job description


Job Title: 
AI Data Engineer

Reports to: Senior Data Engineer

Role Summary:

Data Engineering is a key role in the development team and is responsible for building and maintaining the AI-ready data foundation that powers inKind's intelligent products, machine learning models, and large language model (LLM) applications. The position requires working across departments to build, operate, and optimize highly available data pipelines that feed analytics, ML training and inference, and retrieval-augmented generation (RAG) systems.

Responsibilities: 

  • Responsible for the design, deployment, and maintenance of the business's data and AI platforms
  • Own architectural processes and decisions for various data models within the organization, including schemas, vector stores, and knowledge bases that support AI and LLM use cases
  • Design and operate feature pipelines, embedding pipelines, and evaluation datasets that support machine learning model training, fine-tuning, and continuous evaluation
  • Work cross-functionally with various departments, including but not limited to: leadership, the development team, the finance team, and the data science team, in order to convert data into understandable information and AI-ready inputs for other professionals
  • Ensure implemented data and AI systems have relevant security, privacy, and data-governance controls - particularly around data flowing into and out of third-party LLM providers

Minimum Qualifications:

  • Bachelor's degree in Computer Science, Applied Mathematics, Engineering, or any other technology related field. An equivalent of this educational requirement in working experience is also acceptable
  • 5+ years professional database development experience, preferably as a Data Engineer in a fast-paced environment and complex business setting
  • Expert level knowledge of SQL with focus on writing and optimizing queries
  • Demonstrated experience building and maintaining reliable and scalable ETL/ELT using Snowflake, dbt, and AWS architecture
  • Proficiency in Python and modern AI/ML tooling and experience integrating with LLM APIs (Anthropic, OpenAI, etc.)
  • Expert problem solving ability and maker's mentality; vast experience designing & architecting new features and solutions from scratch - especially those that blend traditional data systems with AI-powered components
  • Eagerness to discover innovative ways to work faster and more efficiently, including leveraging AI coding assistants and agents, while balancing competing concerns (tech debt, cost, security, complexity, etc.)
  • Proactive communication, both written and spoken, and excellent ability to work well with others, in-person and remotely
  • Courage when it comes to raising concerns and asking questions
  • Ability to stay up-to-date with new frameworks and tools - especially in the rapidly evolving AI/ML space - to speed up development, while keeping a sharp eye out for potential vulnerabilities and edge cases (including prompt injection and data leakage to third-party AI services)
Benefits & Perks at inKind

At inKind, we believe supporting our employees goes beyond compensation. We're committed to creating an environment where our team can thrive both professionally and personally.

Health & Wellness
  • 100% employer-paid medical coverage through Blue Cross Blue Shield for employees on our base healthcare plan
  • 100% employer-paid Dental PPO coverage for employees
  • Vision coverage available
  • Company-paid Short-Term Disability coverage
Time Away & Flexibility
  • Unlimited Paid Time Off
  • 9 paid company holidays annually
  • Generous parental leave and child care benefits
Growth & Development
  • Career development and training opportunities designed to support long-term professional growth
Food & Lifestyle Perks
  • Daily catered lunches and office snacks
  • Credits to dine within the inKind restaurant network
Workplace Environment
  • Collaborative, in-person culture based in Austin, Texas
  • Dog-friendly office environment with views of downtown Austin

Salary

$135,000 - $155,000, DOE