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Data Engineer Sports Analytics Jobs in Minnesota

Data Engineer

Minneapolis, MN · On-site

$119K - $143K/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

Minneapolis, MN · On-site +1

$90K - $113K/yr

The Data Engineer will play a foundational role in building and maintaining the data infrastructure that enables advanced analytics, machine learning, and decision intelligence across Ryan Companies.

Data Engineer

Chisago City, MN · On-site

$80K - $120K/yr

Collaborate with IoT engineers on data contracts and payload structure ... Dashboards & Analytics * Build dashboards and visualizations for equipment monitoring. * Develop ...

Responsibilities Data Engineer gains access to data across the organization and provides ongoing ... Analyze business objectives and develop data solutions to meet customer needs. Demonstrated ability ...

Data Engineer

Eagan, MN · On-site

$95 - $110/hr

Strong problem-solving and business analysis skills. Strong decision-making and judgment. Excellent documentation skills. Desired Skills Master's degree in Computer Engineering, Data Science ...

Data Engineer

Rochester, MN · On-site

$111K - $134K/yr

Data Engineer gains access to data across the organization and provides ongoing analysis of the data by monitoring, profiling and analyzing databases. Requires a mix of functional, data and technical ...

Data Engineer

Rochester, MN

$116K - $139K/yr

Data Engineer gains access to data across the organization and provides ongoing analysis of the data by monitoring, profiling and analyzing databases. Requires a mix of functional, data and technical ...

Data Engineer

Rochester, MN

$111K - $134K/yr

Data Engineer gains access to data across the organization and provides ongoing analysis of the data by monitoring, profiling and analyzing databases. Requires a mix of functional, data and technical ...

Data Engineer | TELECOMMUTE

Minneapolis, MN · On-site +1

$119K - $143K/yr

We are a team of 9 Data Engineers and Analysts + Engineering Managers/Leaders * We have 1 product owner on the team and work with several others directly * We have a Scrum Master aligned as well ...

Data Engineer

Minneapolis, MN · Hybrid

$50 - $55/hr

You will collaborate closely with Product Management, Ads Engineering, Analytics, Data Science, and other cross-functional teams to deliver high-quality solutions that meet business needs and support ...

Data Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

You will collaborate closely with Product Management, Ads Engineering, Analytics, Data Science, and other cross-functional teams to deliver high-quality solutions that meet business needs and support ...

Data Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

You will collaborate closely with Product Management, Ads Engineering, Analytics, Data Science, and other cross-functional teams to deliver high-quality solutions that meet business needs and support ...

Lead Data Engineer

Eagan, MN · Hybrid

$116K - $140K/yr

Lead Data Engineer We are seeking a highly skilled and strategic Lead Data Engineer to join our ... Conduct in-depth analysis of large, complex datasets to uncover critical trends, patterns, and ...

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Showing results 1-20

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.

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 Minnesota? For Data Engineer Sports Analytics jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Data Engineer Sports Analytics jobs? Cities in Minnesota with the most Data Engineer Sports Analytics job openings:
Infographic showing various Data Engineer Sports Analytics job openings in Minnesota as of July 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.

Data Engineer

Dlapiper

Minneapolis, MN • On-site

$119K - $143K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 28 days ago


Job description

DLA Piper is, at its core, bold, exceptional, collaborative and supportive. Our people are the backbone, heart and soul of our firm. Wherever you are in your professional journey, DLA Piper is a place you can engage in meaningful work and grow your career. Let's see what we can achieve. Together.

Summary

The Data Engineer, Solutions & Data role designs, builds, and operates data pipelines and data integration processes that translate raw data into trusted, usable datasets for analytics, reporting, and downstream solutions. The role focuses on operationalizing pipelines with governance and service expectations (SLAs), improving data quality and reusability, and enabling secure access to integrated data in support of business initiatives. In current initiatives, data engineering includes consolidating data from multiple sources into a central SQL-based integration point and performing field mapping and transformations, so solution teams can consume data consistently.

Location

This position can sit in any of our U.S. offices and offers a hybrid work schedule.


Responsibilities

Data Pipeline Engineering & Integration

  • Build and operationalize data pipelines across heterogeneous environments, aligning to governance principles and service expectations (SLAs).

  • Build and maintain ingestion, transformation, and publication of pipelines (data engineering practice) to deliver analytics-ready data.

  • Consolidate data from multiple sources into a centralized integration point (e.g., a single SQL Server instance) and manage field mappings and transformations to support consistent downstream consumption.

Data Platform & Storage

  • Design and implement data pipelines using Azure data technologies (e.g., Azure Data Factory, Azure Databricks, Azure Event Hubs, SSIS) to ingest, process, and deliver data from sources such as APIs and other systems.

  • Build and maintain data warehousing capabilities (e.g., Azure Synapse Analytics) to support analytics and reporting workloads.

Data Quality, Reliability & Operations

  • Identify, troubleshoot, and resolve data issues including data quality, integrity, latency, and security concerns; apply monitoring and operational best practices to keep pipelines reliable and performant.

  • Contribute to data quality and governance practices, including profiling datasets, defining quality rules, and establishing monitoring/remediation approaches.

Collaboration & Delivery (Agile Pod Model)

  • 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 reusable data assets and integration components that can be leveraged across multiple initiatives.

Desired Skills

  • Proficiency in SQL and Python.

  • Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks, Azure Event Hubs, SSIS).

  • Data warehousing experience (Azure Synapse Analytics) and strong fundamentals in data modeling, warehousing, and governance.

  • Scripting/automation skills (PowerShell and related tooling) for platform operations and troubleshooting.

  • Preferred experience includes familiarity with additional programming languages such as Java, Scala, or Go; experience integrating data from multiple enterprise source systems into a central SQL-based integration layer; and familiarity with DataOps concepts and operating in cross-functional teams that include data engineering personas.

  • The measures of success for this role include delivering data pipelines with trusted, quality data with agreed service levels, enabling faster onboarding of new data and more consistent analytics/AI consumption and creating reduced manual effort through reusable integrations and standardized transformations, improved data reliability and operational readiness.


Minimum Education

  • High School or GED


Preferred Education

  • Bachelor's Degree in Computer Science, Engineering, or related field.


Minimum Years of Experience

  • 3 years of experience in data engineering and/or data platform engineering (pipelines, integration, and operational support).


Essential Job Expectations

While the specific job requirements of a DLA Piper position may vary depending upon scope of the job and area of specialty, there are certain universal requirements that are expected of all DLA Piper employees, which include but are not limited to:

  • Effectively communicate, verbally and in writing, with clients, lawyers, business professionals, and third parties;

  • Produce deliverables, answer phone calls, and reply to correspondence in an efficient and responsive manner;

  • Provide timely, accurate, and quality work product;

  • Successfully meet deadlines, expectations, and perform work duties as required;

  • Foster positive work relationships;

  • Comply with all firm policies and practices;

  • Engage in both physical and sedentary activity, such as (a) working at a computer for extended periods of time, including on-screen reading and typing; (b) participating in digital/virtual conference calls; (c) participating in meetings as needed;

  • Ability to work under pressure and manage competing demands in a fast-paced environment;

  • Perform all other duties, tasks or projects as assigned.

Our employees are expected to embrace and uphold our firm values as a part of our DLA Piper culture. We are committed to excellence in how we represent our clients and develop our people.

Physical Demands

Sedentary work: Exerting up to 10 pounds of force occasionally and/or a negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Sedentary work involves sitting most of the time. Jobs are sedentary if walking and standing are required only occasionally and all other sedentary criteria are met.


Work Environment

The individual selected for this position may have the opportunity for a hybrid work arrangement comprised of remote and in-office work, the requirement for which will be determined in coordination with the hiring manager or supervisor and may be modified in the firm's discretion in the future.
Disclaimer

The purpose of this job description is to provide a concise statement of the work elements and to organize and present the information in a standardized way. It is not intended to describe all the elements of the work that may be performed by every individual in this classification, nor should it serve as the sole criteria for personnel decisions and actions. The job duties, requirements, and expectations for this position may be modified at the Firm's discretion at any time. This job description does not change the at-will nature of employment.

Application Process

Applicants must apply directly online instead of sending application materials via email.

Accommodation

Reasonable accommodations may be made upon request to permit individuals with a disability to perform the essential functions and responsibilities of the position or to participate in the job selection process. If you have a request for an accommodation during the application process, please contact careers@us.dlapiper.com.

Agency applications will not be considered.

No immigration sponsorship is available for this position.


The firm's expected hiring range for this position is $100,787 - $160,255 depending on the candidate's geographic market location.

The compensation offered for employment will also be dependent on other factors including the candidate's experience, skills, educational and professional background, and overall qualifications. We offer a comprehensive package of benefits including medical/dental/vision insurance, and 401(k).

Applicants who are not based in the jurisdiction in which this position is posted and who apply for this role are doing so voluntarily and are not eligible for relocation assistance. Any relocation benefits, if any, are provided only where a relocation is required at the firm's direction and in accordance with applicable policy and law.

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DLA Piper is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.Job applicant poster viewing center.