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Analytics Engineer Jobs in Colorado (NOW HIRING)

You'll start by doing great data analysis - clean, well-reasoned, fast - and expand into the full analytics engineering lifecycle over time. It's hands-on and high-visibility: you'll collaborate ...

Data/Analytics Engineer Job Location: Westminster CO, or Christchurch NZ Our Department: Field Systems Data/Analytics Engineer - Customer 360 Data Pipelines About the Team: The Field Systems Data ...

Data Analytics Engineer

Fort Collins, CO · On-site

$102K - $146K/yr

We are looking for an Analytics Engineer to join our growing data team and help transform payments data into reliable, scalable, and actionable insights. Sitting at the intersection of data ...

We are looking for an Analytics Engineer to join our growing data team and help transform payments data into reliable, scalable, and actionable insights. Sitting at the intersection of data ...

Analytics Engineer

Broomfield, CO · On-site

$70K - $103K/yr

You'll start by doing great data analysis - clean, well-reasoned, fast - and expand into the full analytics engineering lifecycle over time. It's hands-on and high-visibility: you'll collaborate ...

Senior Analytics Engineer

Denver, CO · On-site +1

$135K - $180K/yr

About the Role Orchard is looking for a Senior Analytics Engineer to help rebuild how the business gets answers from its data. We're moving from a sprawling Looker footprint to a set of certified ...

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Analytics Engineer information

What are the key skills and qualifications needed to thrive as an Analytics Engineer, and why are they important?

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

How does an Analytics Engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

What is an Analytics Engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.
What are the most commonly searched types of Analytics Engineer jobs in Colorado? The most popular types of Analytics Engineer jobs in Colorado are:
What are popular job titles related to Analytics Engineer jobs in Colorado? For Analytics Engineer jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Analytics Engineer jobs? Cities in Colorado with the most Analytics Engineer job openings:
Analytics Engineer

$70K - $103K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 5 days ago


Job description

We're looking for a great data analyst. Not good at SQL - good at analysis. SQL is the tool; analytical thinking is the talent. Candidates who can't demonstrate sharp, independent analytical thinking will not advance
THE ROLE

Recurly's Business Analytics team delivers critical insights to internal and external stakeholders - and we need someone sharp to help us do it better. You'll work with raw data ingested by our data engineering team, building and maintaining the models and views that power ad-hoc analysis and dashboard reporting across the business.

This is a grow-from-the-ground-up investment. You'll start by doing great data analysis - clean, well-reasoned, fast - and expand into the full analytics engineering lifecycle over time. It's hands-on and high-visibility: you'll collaborate directly with stakeholders, own your outputs, and be expected to deliver.

We're also an AI-forward team. Recurly provides a generous Anthropic token budget, and we expect this person to use it. You should already be comfortable using LLMs to accelerate your workflow - writing better SQL faster, exploring unfamiliar datasets, drafting documentation. Knowing how to prompt well is now part of the job.

WHO YOU ARE

Above all else, you are a data analyst. Not someone who runs queries - someone who genuinely thinks analytically. You get handed a vague question and you know how to decompose it, find the right data, spot what's wrong with it, and surface an insight that actually matters. That part isn't something we can train. Either you have it or you don't, and we're looking for someone who has it.

Beyond the analytical core: you're sociable, curious, and energetic. You ask good questions, listen well, and can walk a non-technical stakeholder through your findings without losing them. You already use AI tools to work faster and smarter - not because someone told you to, but because you figured out they were useful. You take ownership, communicate proactively, and want to build a real career in this craft.

Requirements

YOU MUST HAVE

  • Innate analytical ability - you see patterns others miss, ask the question behind the question, and know when a number doesn't smell right
  • The instinct to frame a problem correctly before ever touching data, and the discipline to sanity-check your own conclusions
  • Strong SQL - CTEs, window functions, aggregations; fluent enough that the tool never slows down the thinking
  • Foundational knowledge of dimensional data modeling and data warehouse best practices
  • The ability to write and execute data validation tests and actually resolve what you find
  • Customer-facing poise - comfortable collaborating with business stakeholders and translating between technical and non-technical
  • Energy, initiative, and hunger to learn

NICE TO HAVE (WE'LL TEACH THE REST)

  • BigQuery, dbt (CLI in a git-based workflow), or Looker / OMNI experience
  • Python or R for data work
  • Exposure to payments or subscription data
  • Familiarity with git and version control

THE STACK

  • BigQuery - cloud data warehouse
  • dbt - transformation and modeling layer
  • OMNI / Looker - BI and dashboards

WHO YOU ARE
Above all else, you are a data analyst. Not someone who runs queries - someone who genuinely thinks analytically. You get handed a vague question and you know how to decompose it, find the right data, spot what's wrong with it, and surface an insight that actually matters. That part isn't something we can train. Either you have it or you don't, and we're looking for someone who has it.
Beyond the analytical core: you're sociable, curious, and energetic. You ask good questions, listen well, and can walk a non-technical stakeholder through your findings without losing them. You already use AI tools to work faster and smarter - not because someone told you to, but because you figured out they were useful. You take ownership, communicate proactively, and want to build a real career in this craft.

Benefits

As a full-time employee, Recurly offers competitive benefits programs, perks and options designed to fit your needs and the needs of your family. We offer medical, dental and vision benefits and a menu from which to choose options that work best for you and eligible dependents. We also offer life insurance, short and long-term disability, hospital indemnity, critical illness coverage, employee accident protection, health savings account (HSA) with company contribution & flexible spending account (FSA) options, employee assistance program, Legal and Pet Insurance.

Compensation range: $70,000 to $103,000 per year

Other perks may include:

401(k) Retirement Plan and company match

Flex Time Off

Company Events

Training/Development

Tuition reimbursement

Commuter benefits

Volunteer opportunities

Recurly is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to gender, age, race, religion, or any other classification which is protected by applicable law. Recurly is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process.