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Data Engineer Sports Analytics Jobs in Florida (NOW HIRING)

Data Engineer

Tampa, FL · On-site

$108K - $129K/yr

Data Engineer Company: Peoples Gas System State and City: Florida - Tampa Shift: 8 Hr. X 5 Days WHO ... Perform upgrades to DBMS and data integration products, which include impact analysis, testing ...

Data Engineer

Miami, FL · On-site

$120K - $180K/yr

We are seeking a Data Engineer to join our dynamic team. The ideal candidate is an enthusiastic ... Analytics & Visualization * Collaborate with the analytics team to create, optimize, and maintain ...

Data Engineer

Miami, FL · On-site

$109K - $131K/yr

... Analytics Engineers and Analysts to understand downstream data requirements and model data accordingly. • Support infrastructure-as-code practices and contribute to CI/CD pipelines for data assets ...

Data Engineer

Lake Mary, FL · On-site

$55 - $65/hr

... analytics solutions across a complex SAP environment. This is more than a report development ... As a trusted IT and Engineering services provider, Brooksource supports Fortune 500 organizations ...

Data Engineer

FL

$64K - $129K/yr

Role Summary The Data Engineer supports the delivery of modern data solutions across commercial ... Partner with customer engineering and analytics teams to support onboarding and operationalization ...

Azure Data Engineer

Melbourne, FL · On-site

$62K - $141K/yr

Azure Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and ... You'll sharpen your skills in analytical exploration and data examination while you support the ...

Sr Data Engineer

Atlanta, GA · On-site

$130K/yr

This role partners closely with Data Scientists, Engineers, Analysts, Developers, and business stakeholders to deliver trusted, high-quality data solutions that drive operational efficiency and data ...

Sr Data Engineer

Estero, FL · On-site

$130K/yr

This role partners closely with Data Scientists, Engineers, Analysts, Developers, and business stakeholders to deliver trusted, high-quality data solutions that drive operational efficiency and data ...

Data Engineer

Doral, FL · On-site

$105K - $127K/yr

Dive into exciting opportunities in Cybersecurity, IT, Data Analytics and more. Propel your career ... MANTECH seeks a motivated, career and customer-oriented Journeyman Data Engineer to join our team ...

Analyze how internal and external needs are evolving and recommend changes to systems and storage ... Strong data engineering skills in Python and SQL, with scripting experience for data extraction ...

New

Lead Data Engineer

Orlando, FL · On-site

$148K - $198K/yr

Analyze how internal and external needs are evolving and recommend changes to systems and storage ... Strong data engineering skills in Python and SQL, with scripting experience for data extraction ...

New

Lead Data Engineer

Orlando, FL · On-site

$148K - $198K/yr

Analyze how internal and external needs are evolving and recommend changes to systems and storage ... Strong data engineering skills in Python and SQL, with scripting experience for data extraction ...

New

Data Engineer (Hybrid)

Lake Mary, FL · On-site

$90K - $115K/yr

Analyze, troubleshoot, and optimize BI and digital marketing applications to ensure data accuracy and system performance. * Collaborate with a team of data engineers to support business initiatives ...

Data Engineer

Tampa, FL · On-site

$108K - $129K/yr

We are looking for a Data Engineer with strong handson experience designing, developing, and ... Develop and manage structured and unstructured data pipelines supporting analytics, ML, and ...

Data Engineer (Hybrid)

Lake Mary, FL · On-site

$92K - $116K/hr

Analyze, troubleshoot, and optimize BI and digital marketing applications to ensure data accuracy and system performance. * Collaborate with a team of data engineers to support business initiatives ...

Showing results 41-60

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

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

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

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

Infographic showing various Data Engineer Sports Analytics job openings in Florida as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

$106K - $128K/yr

Full-time

Re-posted 17 days ago


Job description

General Description:

The Data Engineer will play a critical role within the Information Technology organization, partnering closely with data and analytics leadership to build and optimize scalable, reliable data pipelines and platforms that support enterprise analytics and decision-making. This role focuses on enabling data availability, quality, and accessibility across business domains, ensuring alignment with strategic data initiatives. The engineer will work with cross-functional teams to gather and translate business data requirements into technical solutions, support data integration efforts, and uphold data governance standards. Responsibilities may include contributing to the development of data products, enhancing data infrastructure, and supporting data platform modernization efforts to ensure trusted, timely data is accessible for business use.

 

Essential Duties and Responsibilities:

Guidewire Data Warehouse Management: Continue to support and enhance the Guidewire Enterprise Data Warehouse, ensuring data availability, accuracy, and efficiency in ETL operations.

Data Platform Implementation: Architect, design, and implement a scalable, on-prem or cloud-based enterprise data platform, integrating diverse data sources beyond Guidewire Insurance Suite

Data Integration & Engineering: Develop and oversee ETL/ELT pipelines to ingest, transform, and store data efficiently, leveraging modern tools.

Data Modeling & Architecture: Design and implement optimized data models for structured and unstructured data, supporting reporting, analytics, and AI/ML initiatives.

Data Governance & Security: Establish best practices for data governance, data quality, metadata management, and security compliance across all data assets.

Advanced Analytics Support: Enable self-service analytics, real-time data processing, and AI/ML-driven insights by integrating modern data technologies such as data lakes, streaming data, Graph and NoSQL databases.

Collaboration & Leadership: Act as a strategic partner to IT, business units, and analytics teams, aligning data initiatives with organizational goals. Mentor junior team members and foster a culture of data-driven decision-making.

Monitor the task queue, take, and update tickets as directed by your supervisor.

Successfully engage in multiple initiatives simultaneously.

Contributes to the development of project plans and may assign and monitor tasks.

Assist in the development and generation of new reports to be provided to senior management across functional departments.

Performs other duties as required.

Supplemental Information:

This job description has been prepared to indicate the general nature and level of the work that the employees perform within their classification.   This description is not and cannot be interpreted as an inventory of all the duties, tasks, responsibilities, and qualifications required for the employees assigned to this job.

Education and / or Experience:

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or a related field.

5+ years of experience in data architecture, engineering, or related roles, preferably within the insurance industry.

Strong expertise in the Guidewire InsuranceSuite database schemas (PolicyCenter, BillingCenter, ClaimCenter) is a plus.
 

Ability to analyze and learn new complex data sources models and integrate them into the data platform’s pipelines.

Experience implementing cloud-based data platforms in Azure and familiarity with data lakehouse architectures.

Proficiency in modern ETL/ELT tools (e.g., MS SSIS and Azure Data Factory) and database technologies (SQL, Databricks, etc.).

Hands-on experience with big data processing, streaming technologies (Kafka, Spark, Flink), and API-driven data integration.

Strong understanding of data security, compliance, and governance best practices (GDPR, CCPA, SOC2, etc.).

Familiarity with BI/reporting tools such as Power BI, Tableau, Looker.

Strong knowledge and experience implementing Data Mesh architecture is a plus.

Knowledge of machine learning frameworks and MLOps is a plus. 

Familiarity with ticketing systems like Atlassian Jira used to assign and track work amongst multiple team members.

Must be resourceful, industrious, and willing to take on new tasks and proactively learn new technologies to keep up with business needs.

Must be able to work under tight deadlines efficiently and with high quality.

Must possess strong organizational skills with demonstrated attention to detail.

Must be flexible and able to adapt in a changing business environment.

Must possess a positive attitude and strong work ethic.

P&C Experience is a must. 

Excellent verbal and written communication skills and the ability to interact professionally with a diverse group (executives, managers, and subject matter experts).

Must be proficient in Microsoft Office (Excel, Word, Power Point).

Licenses and / or Certifications:  

Azure Data Engineer Associate or higher preferred.