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Data Analytics Developer Jobs in Colorado (NOW HIRING)

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 ...

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 ...

AI Data Analytics Engineer

Fort Collins, CO

$113K - $135K/yr

We are hiring an AI Data Analytics Engineer to design, build, and ship the data, analytics, and AI capabilities that power BillGO's AI/Data Platform, from trusted data models and self-serve analytics ...

We are hiring an AI Data Analytics Engineer to design, build, and ship the data, analytics, and AI capabilities that power BillGO's AI/Data Platform, from trusted data models and self-serve analytics ...

You will connect strategy to execution across Data Engineering, Analytics Engineering, and Data Visualization, ensuring teams deliver trusted, scalable data products that enable smarter, faster ...

Data Analytics Engineer - Boulder, Colorado

Boulder, CO · On-site

$120K - $144K/yr

They are seeking a Data Analytics Engineer to build and maintain data models, develop dashboards, and support data operations, ensuring reliable data for business insights. Responsibilities : • ...

Senior Data Analytics Engineer

Boulder, CO · On-site +1

$109K - $149K/yr

As an Analytics Engineer, you will play a crucial role in transforming raw data into actionable insights to support data-driven decision-making across the company. You will work independently on ...

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Data Analytics Developer information

See Colorado salary details

$25

$57

$99

How much do data analytics developer jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for data analytics developer in Colorado is $57.57, according to ZipRecruiter salary data. Most workers in this role earn between $46.25 and $65.19 per hour, depending on experience, location, and employer.

What is the difference between Data Analytics Developer vs Data Analyst?

AspectData Analytics DeveloperData Analyst
Required SkillsSQL, programming, data modeling, visualization toolsExcel, SQL, basic statistics, visualization
CertificationsData analytics, programming certificationsExcel, Tableau, Power BI certifications
Work EnvironmentDevelops data tools, pipelines, and dashboardsAnalyzes data, creates reports, interprets findings
Industry UsageTech, finance, healthcare, where data tools are neededBusiness, marketing, finance, where insights are required

While both roles work with data, Data Analytics Developers focus on building data systems and tools, whereas Data Analysts interpret data to provide insights. The roles often overlap but differ mainly in technical development versus analysis and reporting.

What are some common challenges Data Analytics Developers face when integrating new data sources into existing analytics platforms?

Data Analytics Developers often encounter challenges such as data inconsistency, varying data formats, and incomplete documentation when integrating new sources. Ensuring data quality and compatibility with existing pipelines requires close coordination with data engineers and source system owners. Additionally, they must balance the need for rapid integration with maintaining data security and compliance standards. Overcoming these challenges typically involves thorough data profiling, robust ETL processes, and proactive communication across teams.

What does a Data Analytics Developer do?

A Data Analytics Developer is responsible for designing, developing, and implementing data analysis tools and solutions. They work with large datasets to extract insights, create data models, and build dashboards or reports that help organizations make data-driven decisions. Their role often involves collaborating with data scientists, business analysts, and IT teams to ensure data accuracy, performance, and security. They typically use programming languages like Python or SQL and may work with business intelligence platforms such as Tableau or Power BI.

What are the key skills and qualifications needed to thrive as a Data Analytics Developer, and why are they important?

To thrive as a Data Analytics Developer, you need strong analytical skills, proficiency in programming languages like Python or R, and a solid background in statistics or mathematics, typically supported by a relevant degree. Experience with data visualization tools (such as Tableau or Power BI), SQL, and cloud-based analytics platforms, as well as certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate, are highly beneficial. Excellent problem-solving abilities, attention to detail, and effective communication skills set top performers apart in this field. These skills ensure accurate data analysis, actionable insights, and successful collaboration with stakeholders to drive data-informed decision-making.
What are popular job titles related to Data Analytics Developer jobs in CO? For Data Analytics Developer jobs in CO, the most frequently searched job titles are:
Infographic showing various Data Analytics Developer job openings in Colorado as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $119,740 per year, or $57.6 per hour.
Data Analytics Engineer

Data Analytics Engineer

BillGO, Inc.

Fort Collins, CO • On-site

$102K - $146K/yr

Full-time

Medical, Retirement

Posted 10 days ago


Job description

BillGO is building the next generation of payment and money movement infrastructure for small businesses. Data products and insights are core to how we scale reliability, reduce operational friction, and deliver better outcomes across payments, risk, and support. 

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 engineering, analytics, and business, you will build clean data models, define key metrics, and enable stakeholders across product, finance, risk, and operations to make data-driven decisions. 

 This role is ideal for someone who understands the complexity of payments ecosystems (transactions, settlements, fraud, reconciliation) and enjoys turning messy data into trusted, well-documented datasets. 


Why This Role Matters

This role matters because it transforms complex, fragmented payments data into a trusted foundation for decision-making across the business. As an Analytics Engineer, you enable teams to operate with clarity and confidence by building reliable data models, defining consistent metrics, and ensuring data integrity in a highly intricate financial ecosystem. In a space where accuracy, speed, and compliance are critical, your work directly impacts everything from revenue visibility and reconciliation to fraud detection and operational efficiency. By bridging the gap between raw data and business insight, this role not only improves day-to-day performance but also helps scale the company’s data infrastructure, empowering smarter decisions and driving long-term growth in a rapidly evolving fintech landscape.


What You’ll Do

  • Design, build, and maintain scalable data models for customers, payments, transactions, settlements, and financial reporting  
  • Transform raw data into clean, reliable datasets and data models. 
    • +Using tools like Claude, Coalesce, and Tableau  
    • Using data warehouses like Snowflake, AWS RDS, AWS DynamoDB 
    • Also incorporating other data sources from AWS S3, like csv, Json, and parquet files. 
  • Develop data dictionaries, semantic layers, and data catalogs 
  • Partner with Product, Finance, Risk, and Operations teams to define key metrics and enable insights and dashboards for decision-making and predictions.  
  • Ensure data quality and integrity through testing, monitoring, and documentation  
  • Optimize data pipelines for performance and cost efficiency  
  • Translate business requirements into data solutions that scale with company growth  
  • Support regulatory and financial reporting needs (e.g., reconciliation, audit readiness)  
  • Contribute to data governance, definitions, and metric standardization

What You Bring

  • 3+ years of experience in an analytics engineering, data analytics, or data engineering role 
  • Strong SQL skills, data analytics skills, ability to interrogate data and derive impactful insights.  
  • Experience with Coalesce or similar transformation frameworks  
  • Experience with data warehousing (Snowflake)  
  • Experience modeling complex datasets (fact/dimension modeling, star schemas)  
  • Experience building metrics layers or semantic models  
  • Understanding of ELT pipelines and data orchestration tools 
  • Experience with Python for data processing  
  • Experience with version control using Github and Github actions 
  • Ability to translate ambiguous business questions into structured data models  
  • Strong attention to detail and data accuracy  
  • Experience working with cross-functional stakeholders  

Preferred Qualifications 

  • Data Science and Machine Learning hands-on experience.  
  • Familiarity with event-driven architectures or streaming data  
  • Experience working with payments data 
  • Familiarity with concepts like:  
  • Authorization & settlement flows  
  • Interchange & fees  
  • Chargebacks & disputes  
  • Fraud detection signals  
  • Ledgering and reconciliation  
  • Exposure to compliance or financial reporting requirements  

Compensation

We offer a competitive compensation package, including:

  • Base salary ($102,000-$146,900)
  • Performance incentive
  • Equity opportunities
  • Comprehensive health, retirement, and lifestyle benefits

This role is about more than compensation, it’s about the opportunity to transform how small businesses thrive in the digital economy.