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Non Union Football Data Analytics Jobs (NOW HIRING)

Bank of Montreal

Manager, Data & Analytics

Chicago, IL · On-site

$74K - $138K/yr

Data Analytics & Reporting This is a hybrid role requiring 3-4 days in the Chicago or San Fran ... Works independently and regularly handles non-routine situations. * Broader work or ...

TECO

Data Analytics Architect

Tampa, FL

... to non-technical stakeholders POSITION CONCEPT The Data and Analytics Architects responsible for the "back end" components of the organizations BIA environment from standards, architecture, and ...

CACI International, Inc.

Data Analytics

Albuquerque, NM · On-site

$71K - $150K/yr

Job Title: Data Analytics Job Category: Information Technology Time Type: Full time Minimum ... Prepare clear, non-technical reports outlining solution options, feasibility, and probability of ...

TECO

Data Analytics Architect

Tampa, FL · On-site

... to non-technical stakeholders POSITION CONCEPT The Data and Analytics Architects responsible for the "back end" components of the organizations BIA environment from standards, architecture, and ...

Kia America

Data & Analytics Specialist

Irvine, CA · On-site

Translate complex analysis into business-relevant insights that non-technical stakeholders can act on. * Analyze large amounts of data to discover trends and patterns. * Analytics will be primarily ...

Santa Fe County

Data Manager

Santa Fe, NM · On-site

$86K - $103K/yr

NON-UNION Department Contact Information: Stephanie Stancil 505-995-2710 Union Eligibility ... Conduct analyses of data to provide expected ranges of datasets, equity reviews, or ...

New

4pconsultinginc

Data Analytics Analyst 3

Atlanta, GA · On-site

Present data insights and trends to technical and non-technical stakeholders Data Integration & ETL * Design and execute ETL (Extract, Transform, Load) processes to prepare data for analysis

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Non Union Football Data Analytics information

What are the key skills and qualifications needed to thrive as a Non Union Football Data Analyst, and why are they important?

To thrive as a Non Union Football Data Analyst, you need strong quantitative analysis skills, a background in statistics or data science, and a deep understanding of football tactics and performance metrics. Proficiency with data analytics tools such as Python, R, SQL, and specialized sports analytics software is typically required. Excellent attention to detail, effective communication, and the ability to translate complex data into actionable insights are critical soft skills for this role. These skills and qualities are essential for identifying trends, informing coaching decisions, and providing a competitive edge through data-driven strategies.

What is non union football data analytics?

Non union football data analytics involves collecting, processing, and interpreting data related to football (soccer or American football) performance, statistics, and strategy, outside of unionized organizations. Professionals in this field use statistical methods, software tools, and data visualization techniques to help teams, coaches, and management make better decisions. This role typically focuses on providing insights about player performance, match outcomes, and tactical trends, often for private companies, media, or non-union clubs. The 'non union' aspect means that the role is not governed by a labor union, which can affect job conditions and benefits.

Do NFL teams hire data analysts?

Yes, NFL teams hire data analysts to evaluate player performance, develop strategies, and improve decision-making using statistical tools and data analysis techniques. These roles often require knowledge of sports analytics software, programming languages like Python or R, and a strong understanding of football metrics.

What are some typical challenges faced by professionals in Non Union Football Data Analytics roles?

Professionals in Non Union Football Data Analytics often encounter challenges such as consolidating and cleaning large, disparate datasets from different sources to ensure data accuracy. They must also communicate complex analytical findings to coaches and management in clear, actionable terms. Collaboration with scouts, coaching staff, and IT teams is frequent, requiring strong interpersonal skills and adaptability. Additionally, staying updated with the latest analytical tools and football trends is essential for delivering valuable insights that can influence team strategies.

How to get into data analysis in football?

To pursue a career in football data analysis, develop skills in statistics, data management, and programming languages like Python or R. Gain experience with sports analytics tools, understand football tactics, and consider obtaining certifications in data analysis or sports management to enhance your qualifications.

Can a data analyst become a sports analyst?

A data analyst can transition into a sports analyst role by gaining knowledge of sports-specific metrics, understanding game strategies, and developing expertise in sports data sources. Skills in data visualization, statistical analysis, and tools like SQL or Python are valuable in both roles. Certifications or experience in sports analytics can also facilitate this career shift.

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. Entry-level analysts may start lower, while experienced professionals with advanced skills in data visualization and statistical software can earn higher salaries in sports organizations or consulting firms.
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Non Union Football Data Analytics jobs near you

Data Analytics Architect

Rivago infotech inc

Southlake, TX • On-site

Other

Posted 5 days ago

New

Job description

Mandatory Skills 

  • 15+ yearsin Data Architecture, Data Analytics, Data governance, and Data Warehousingand architectural thought leadership 

  • Proven experience withdata strategy, roadmap, and end-to-end data landscape 

  • Strong hands-on experience withGoogle Cloud Platform, especiallyBig Query 

  • ExpertiseinInformatica IDMC 

  • AdvancedComplex SQLandPythonskills 

  • Experience designingenterprise data warehouse & analytics solutions 

  • Ability to support and guidedevelopment and production systems 

  • Strongbusiness, communication, and stakeholder managementskills 

  • Google Cloud Platform Certification(Professional Data Engineer / Cloud Architect) 

Good to Have Skills 

  • Experience with Google Cloud Platform Pub/Sub and Cloud Composer  

  • Exposure to AI/ML ready data architectures  

  • BQ Data Modeling and EDC 

  • Cloud cost optimization experience 

  • Consulting or large enterprise experience 

  • Exposure to security and compliance frameworks in enterprise data platforms 

 
 
Role Overview

We are seeking an experienced Senior Data Analytics Architect with over 15 years of expertise in designing and delivering enterprise-scale data, analytics, and AI-enabled solutions. This role will lead the architecture, design, and implementation of modern data analytics platforms on Google Cloud Platform (Google Cloud Platform), enabling advanced analytics, data warehousing, and artificial intelligence use cases.

The Senior Data Analytics Architect will work closely with Product teams, development and production support teams, business users, and data consumers to ensure data solutions are scalable, reliable, secure, and aligned with business objectives.

Key ResponsibilitiesData & Analytics Architecture
  • Define and own the enterprise data and analytics architecture, aligning with business strategy and long-term analytics roadmap.
  • Architect end-to-end data warehousing, analytics, and AI-ready data platforms.
  • Design logical, physical, and analytical data models to support reporting, dashboards, advanced analytics, and AI/ML workloads.
  • Establish architecture standards, design patterns, and best practices for analytics and data platforms.
  • Architect data ingestion, streaming, and batch pipelines using Informatica IDMC, Pub/Sub, and Cloud Composer
 Solution Design & Implementation
  • Design and implement cloud-native analytics solutions on Google Cloud Platform, with a strong focus on Big Query.
  • Architect scalable data warehouses and analytics layers optimized for high-performance querying.
  • Design and oversee data ingestion, transformation, and orchestration pipelines using Informatica IDMC.
  • Enable analytics and AI use cases by ensuring data is well-structured, governed, and accessible.
Data Analytics & Artificial Intelligence Enablement
  • Support advanced analytics and AI initiatives by designing data architectures optimized for machine learning and data science workloads.
  • Collaborate with analytics and AI teams to ensure data availability, quality, and performance.
  • Ensure the data platform supports exploratory analytics, predictive modeling, and AI-driven insights.
 Development & Production Support
  • Provide hands-on architectural guidance to development teams throughout the development lifecycle.
  • Review SQL, Python code, and data pipelines for performance, scalability, and reliability.
  • Support production environments, including:
    • Monitoring and troubleshooting data pipeline failures.
    • Performance tuning and optimization
    • Root cause analysis and issue resolution
  • Ensure SLA adherence, data accuracy, and high availability of analytics systems.
 Stakeholder Collaboration
  • Partner with Product teams to translate product and analytics requirements into robust data solutions.
  • Work closely with business users and data consumers to understand reporting, analytics, and insight needs.
  • Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
  • Act as a trusted advisor for data, analytics, and AI capabilities.
 Data Governance, Quality & Security
  • Define and enforce data governance, data quality, and metadata management standards.
  • Ensure compliance with enterprise security, privacy, and regulatory requirements.
  • Promote best practices for data lineage, auditing, and access control across analytics platforms.
Required Skills & QualificationsExperience
  • 15+ years of experience in Data Architecture, Data Analytics Architecture, and Data Warehousing.
  • Proven experience delivering enterprise-scale data and analytics solutions.
  • Strong background in supporting both development and production environments.
 Technical Skills
  • Strong hands-on experience with Google Cloud Platform, including Big Query, Pub/Sub, and Cloud Composer
  • Strong experience with:
    • Big Query (analytics design, optimization, cost, and performance tuning)
    • Informatica Intelligent Data Management Cloud (IDMC)
  • Advanced proficiency in Complex SQL (query tuning, analytical functions).
  • Strong and experienced Python skills for data processing, automation, and analytics support.
  • Extensive experience with Data Warehousing concepts, including dimensional and analytical data modeling.
  • Experience designing data platforms for data analytics and AI / ML workloads.
 Soft Skills
  • Excellent communication and stakeholder management skills.
  • Ability to translate business requirements into technical architecture.
  • Strong analytical, problem-solving, and decision-making abilities.
  • Proven ability to work across cross-functional and geographically distributed teams.
Required Qualifications
  • Experience working in large enterprise or highly regulated environments.
  • Exposure to BI tools, analytics platforms, and data science ecosystems.
  • Familiarity with DevOps, CI/CD pipelines, and production monitoring for data platforms.
  • Experience with data governance, cataloging, and quality tools.

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