Data Analytics Engineer Visa Sponsorship Jobs in Colorado
Data analytics engineer roles in Colorado are concentrated in Denver's thriving tech sector, with employers like Palantir, Arrow Electronics, Envision Healthcare, and a growing cluster of fintech and aerospace firms actively hiring. Boulder's startup ecosystem and Colorado Springs' defense contractors add additional hiring volume. Many of these employers have established H-1B visa and O-1 visa sponsorship histories.
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Get Access To All JobsINTRODUCTION
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.
ROLE AND RESPONSIBILITIES
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
BASIC QUALIFICATIONS
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.
INTRODUCTION
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.
ROLE AND RESPONSIBILITIES
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
BASIC QUALIFICATIONS
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.
Data Analytics Engineer Job Roles in Colorado
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Search Data Analytics Engineer Jobs in ColoradoData Analytics Engineer Jobs in Colorado: Frequently Asked Questions
Which companies sponsor visas for data analytics engineers in Colorado?
Several large Colorado employers have consistent H-1B sponsorship records for data and engineering roles, including Palantir Technologies (Denver), Arrow Electronics, DaVita, and Lockheed Martin's Colorado operations. Denver-based fintech companies and healthcare analytics firms also sponsor regularly. Sponsorship patterns vary by year and role, so checking a company's recent LCA filings with the Department of Labor gives the most accurate picture of their sponsorship activity.
Which visa types are most common for data analytics engineer roles in Colorado?
The H-1B is the most common visa for data analytics engineers in Colorado, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, information systems, or a related field. Candidates with exceptional records may pursue the O-1A. Australians have access to the E-3 visa, which follows a similar employer-sponsored process but has no lottery. TN visa status is available to Canadian and Mexican nationals in qualifying technical roles.
Which cities in Colorado have the most data analytics engineer sponsorship jobs?
Denver accounts for the largest share of data analytics engineer sponsorship jobs in Colorado, driven by its concentration of healthcare technology, fintech, and enterprise software companies. Boulder is a secondary hub with a strong startup and SaaS presence. Colorado Springs has demand from defense and government contractors, though sponsorship rates there tend to be lower given the security clearance requirements common in that market.
How to find data analytics engineer visa sponsorship jobs in Colorado?
Migrate Mate filters job listings specifically for visa sponsorship eligibility, making it straightforward to browse data analytics engineer openings in Colorado without sorting through roles that don't sponsor. You can filter by state and role type to surface relevant positions from employers with active sponsorship histories. This is more efficient than general job searches, where sponsorship availability is rarely stated upfront in the listing.
Are there any Colorado-specific factors that affect sponsorship for data analytics engineers?
Colorado's Equal Pay for Equal Work Act requires employers to disclose compensation ranges in job postings, which gives you useful context when evaluating whether a role meets prevailing wage requirements for H-1B purposes. The state's strong university pipeline from CU Boulder and Colorado State University in data and computer science also means employers are accustomed to hiring internationally trained graduates. Defense-sector roles in Colorado Springs may be harder to sponsor due to clearance restrictions.
What is the prevailing wage for sponsored data analytics engineer jobs in Colorado?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.