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Analytics Engineer Manager Jobs (NOW HIRING)

Product Analytics Engineer

Manhattan, NY ยท On-site

$60 - $75/hr

You will report to the Analytics Engineering Manager, partner closely with Data Engineering, and influence Product, Engineering, and Design stakeholders across each workstream. This opportunity ...

Product Analytics Engineer

New York, NY ยท On-site

$60 - $75/hr

You will report to the Analytics Engineering Manager, partner closely with Data Engineering, and influence Product, Engineering, and Design stakeholders across each workstream. This opportunity ...

Analytics Engineer

Rye, NY ยท On-site

$125 - $150/hr

Responsibilities The Analytics Engineer is a highly technical, business-facing role responsible for ... Strong time management with a focus on delivery and accountability. * Clear written and verbal ...

Analytics Engineer

Rye, NY ยท On-site

$142K/yr

The Analytics Engineer operates with a high degree of independence, demonstrates strong ownership ... Strong time management with a focus on delivery and accountability. * Clear written and verbal ...

Analytics Engineer, Data Analytics Practice Be You. The Data Analytics Practice within Duke ... Demonstrated ability to manage projects independently and work effectively in a collaborative team ...

Analytics Engineer

Miami, FL ยท On-site

$125 - $150/hr

... management at scale across the US and UK. About the Role We're looking for an Analytics Engineer to join our Global Data & Analytics team and help build the data models, pipelines, and semantic layer ...

Analytics Engineer, Data Analytics Practice Be You. The Data Analytics Practice within Duke ... Demonstrated ability to manage projects independently and work effectively in a collaborative team ...

... management at scale across the US and UK. About the Role We're looking for an Analytics Engineer to join our Global Data & Analytics team and help build the data models, pipelines, and semantic layer ...

Analytics Engineer Hybrid Overview Seeking a versatile Analytics Engineer to bridge the gap between ... Support data governance, lineage, documentation, and best practices for enterprise data management.

Description About MLG Capital MLG Capital is a private real estate investment manager focused on ... This is MLG's first-ever Analytics Engineer hire, supporting the modernization of reporting ...

Analytics Engineer

$160K - $180K/yr

You will partner closely with Customer Success Managers, Data Engineers, Product Managers, and ... You are an experienced analytics professional with a deep understanding of healthcare data. * You ...

Analytics Engineer Hybrid Overview Seeking a versatile Analytics Engineer to bridge the gap between ... Support data governance, lineage, documentation, and best practices for enterprise data management.

Analytics Engineer

Houston, TX ยท On-site

$100 - $125/hr

Houston, TX Employment Type: Full-Time Reports To: Sr. Manager, Data & Analytics ABOUT THE ROLE We are seeking an Analytics Engineer to join our Data & Analytics team and play a key role in designing ...

$90K - $110K/yr

Position Summary The Analytics Engineer is responsible for owning the design, build, and ongoing ... Experience in financial services, wealth management, or other regulated industries is a plus.

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Showing results 1-20

Analytics Engineer Manager information

What does an analytics engineer manager do?

An Analytics Engineer Manager leads a team of analytics engineers who build, maintain, and optimize data pipelines, analytics models, and reporting systems. They bridge the gap between data engineering and data analysis by ensuring data is accessible, reliable, and well-documented for business users. Their responsibilities include setting technical strategy, mentoring team members, collaborating with stakeholders, and ensuring best practices in data infrastructure. They also play a key role in making data-driven decisions and aligning analytics initiatives with organizational goals.

How does an analytics engineer manager typically support cross-functional collaboration within an organization?

An Analytics Engineer Manager plays a key role in fostering collaboration between engineering, data science, and business teams. They often act as a bridge, translating complex business requirements into scalable data models and ensuring that analytics solutions align with organizational goals. This role frequently involves coordinating project timelines, mentoring analytics engineers, and facilitating communication to ensure that data-driven insights are both actionable and accessible across departments. By promoting transparency and standardizing data practices, they help teams work more efficiently and effectively together.

What are the key skills and qualifications needed to thrive as an analytics engineer manager, and why are they important?

To thrive as an Analytics Engineer Manager, you need a strong background in data engineering, analytics, and leadership, typically supported by a degree in computer science or related field and experience managing technical teams. Proficiency with data modeling, SQL, ETL tools, cloud data platforms (e.g., Snowflake, BigQuery), and analytics engineering frameworks like dbt is essential. Outstanding communication, project management, and mentorship skills distinguish top performers in this role. These skills ensure efficient team collaboration, high-quality data infrastructure, and delivery of actionable insights to drive business decisions.

What is the difference between Analytics Engineer Manager vs Data Engineer?

AspectAnalytics Engineer ManagerData Engineer
Required CredentialsBachelor's/Master's in CS, Analytics, or related; experience in data analytics toolsBachelor's/Master's in CS, Data Engineering, or related; strong programming skills
Work EnvironmentLeads analytics teams, collaborates with data scientists and business unitsBuilds data pipelines, manages data infrastructure, collaborates with data teams
Employer & Industry UsageUsed in analytics-driven organizations, tech, finance, retailCommon in data-intensive industries, tech, healthcare, finance

The Analytics Engineer Manager focuses on leading analytics teams and translating data into insights, while Data Engineers build and maintain the data infrastructure. Both roles require strong technical skills and collaboration but differ in their primary focus and responsibilities.

What are the most commonly searched types of Analytics Engineer jobs?

The most popular types of Analytics Engineer jobs are:

What are popular job titles related to Analytics Engineer Manager jobs?

For Analytics Engineer Manager jobs, the most frequently searched job titles are:

Infographic showing various Analytics Engineer Manager job openings in the United States as of September 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Analytics Engineer

Englewood, CO โ€ข On-site

$105K - $115K/yr

Full-time

Posted 15 days ago


Job description

JOB SUMMARY: The Analytics Engineer will help pioneer the next generation of analytics, automation, and data-driven decision making at the Denver Broncos. This role will develop and scale solutions that improve revenue generation, fan engagement, operational efficiency, and organizational decision making through a combination of analytics engineering, predictive modeling, and AI-enabled workflows.

This highly visible role will partner with stakeholders across Ticketing, Marketing, Partnerships, Operations, and Leadership to build trusted data products, predictive insights, and intelligent automations that transform how the organization interacts with data.

This is a full-time, onsite position based in Englewood, Colorado.

DUTIES AND RESPONSIBILITIES:ย 

Analytics Engineering & Business Intelligence - Build trusted data products that power business decisions

  • Design, develop, and maintain analytics-ready datasets, semantic models, and reusable business logic that support dashboards, reporting, machine learning models, and AI-enabled workflows
  • Build and maintain ETL pipelines and data integration processes that reliably ingest, transform, and load data into the enterprise data warehouse
  • Partner with analysts, engineers, and business stakeholders to create scalable reporting solutions that improve visibility into ticketing, marketing, sponsorship, ticketing and operational performance
  • Deliver actionable insights by gathering requirements, developing dashboards and visualizations, and supporting ad hoc analytical requests using best practices in data integrity, validation, analysis, and documentation
  • Develop attribution and measurement frameworks that help quantify the impact of fan engagement, marketing communications, and lifecycle campaigns
  • Develop lead scoring and prospecting solutions that support premium, sponsorship, and future stadium sales efforts
  • Develop consumer insights solutions that uncover fan behaviors and trends to inform business strategy and growth initiatives
  • Serve as a trusted analytics partner to stakeholders by translating business needs into scalable and measurable data solutions

Data Science & Predictive Analytics - Develop models that improve business outcomes

  • Develop, maintain, and embed predictive models into solutions that support pricing, demand forecasting, fan engagement, and customer behavior use cases
  • Enhance and manage existing fan segmentation, propensity, and predictive scoring models that support personalized marketing and engagement strategies
  • Partner with business stakeholders to identify opportunities where predictive analytics can improve revenue generation, customer engagement, and operational effectiveness
  • Monitor, evaluate, and refine models to ensure performance, accuracy, and alignment with business goals

AI Enablement & Automation - Apply AI tools to accelerate business processes and decision making

  • Build and maintain trusted data resources that make it easy for employees, analysts, and AI tools to securely access consistent business information and insights.
  • Help establish and maintain guidelines that ensure AI solutions are accurate, secure, reliable, and aligned with business needs and company policies.
  • Leverage emerging analytics and agentic capabilities to transform data into proactive, contextual insights that identify opportunities and deliver timely information to stakeholders

MINIMUM REQUIREMENTS:

  • Bachelor's or Master's in a quantitative field (Computer Science, Statistics, Engineering, Data Science)
  • 3-4 years of professional experience in analytics engineering, advanced analytics, data science, or related fields
  • 1+ years of professional experience deploying products built on predictive modeling and machine learning (MLOps)
  • Experience developing lead scoring models, prospecting strategies, and sales intelligence solutions that support customer acquisition and revenue growth
  • Experience using consumer research, segmentation, and behavioral analytics to generate actionable business insights
  • Expertise in SQL and Python
  • Experience with Snowflake, dbt, and modern analytics engineering practices
  • Experience with agentic workflows, MCP, RAG, or LLM-powered applications
  • Experience building dashboards and reporting solutions using Power BI or Tableau
  • Experience with data modeling, ETL development, and data warehousing
  • Excellent communication and storytelling skills, capable of translating complex technical concepts into intuitive, impactful insights and driving adoption of ML and AI-driven solutions

PREFFERED QUALIFICATIONS:ย 

  • Experience supporting ticketing, marketing, sponsorship, or fan engagement analytics
  • Experience with AI-enabled workflows, Copilot Studio, Claude, Cortex, or similar platforms
  • Familiarity with SDLC, CI/CD, source control, and deployment practices

In accordance with the Colorado Equal Pay for Equal Work Act, the salary range for this role is $105,000 - $115,000.

This posting is anticipated to close on September 6th. Applications may be reviewed on a rolling basis, and the employer reserves the right to close the application window early if a qualified candidate pool is established.