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Data Stacks Jobs in Colorado (NOW HIRING)

Sovrn

Director, Data Collective

Boulder, CO · On-site

You'll be working with a strong senior team, a modern stack, and an organization that already uses LLMs and agentic tooling across the data stack. We're looking for a leader who can take what ...

Blue Margin

Senior Data Engineer

Fort Collins, CO · On-site

$110K - $140K/hr

You will be hands-on with data pipelines, large-scale data processing, and modern cloud data stacks while mentoring team members and helping shape best practices. The Role This role requires strong ...

NuView

Data Analyst

Denver, CO · On-site +1

$80K - $100K/yr

Familiarity across modern data stack including ETL (Stitch, Rivery, Fivetran, etc), Data warehouse (Big Query, Redshift, Snowflake, etc.) and Data Visualization (Tableau, Looker, Power BI, etc.

Sovrn

Director, Data Collective

Boulder, CO

You'll be working with a strong senior team, a modern stack, and an organization that already uses LLMs and agentic tooling across the data stack. We're looking for a leader who can take what ...

Blue Margin

Senior Data Engineer

Fort Collins, CO · On-site

$110K - $140K/yr

You will be hands-on with data pipelines, large-scale data processing, and modern cloud data stacks while mentoring team members and helping shape best practices. The Role This role requires strong ...

NuView Analytics

Data Analyst

Denver, CO · Remote

Familiarity across modern data stack including ETL (Stitch, Rivery, Fivetran, etc), Data warehouse (Big Query, Redshift, Snowflake, etc.) and Data Visualization (Tableau, Looker, Power BI, etc ...

NuView Analytics

Senior Data Analyst

Denver, CO · Remote

Familiarity across modern data stack including ETL (Stitch, Rivery, Fivetran, etc), Data warehouse (Big Query, Redshift, Snowflake, etc.) and Data Visualization (Tableau, Looker, Power BI, etc ...

NuView

Senior Data Analyst

Denver, CO · On-site +1

$90K - $120K/yr

Familiarity across modern data stack including ETL (Stitch, Rivery, Fivetran, etc), Data warehouse (Big Query, Redshift, Snowflake, etc.) and Data Visualization (Tableau, Looker, Power BI, etc.

Sovrn

Principal Data Engineer

Boulder, CO · On-site +1

$140K - $187K/yr

Languages/components/tools in our stack: Python, Pyspark, Kafka, Databricks, AWS What you'll be doing: Data Platform & Architecture * Own the design and evolution of data platform systems that ...

CapTech Consulting

Lead Data Strategist

Denver, CO · On-site

Experience with the modern data stack/platform technologies, products, and approaches. * Delivery experience on multiple cloud platforms (e.g., AWS, Azure, GCP). * Deep background with integrations ...

CapTech Consulting

Lead Data Strategist

Denver, CO · On-site

Experience with the modern data stack/platform technologies, products, and approaches. * Delivery experience on multiple cloud platforms (e.g., AWS, Azure, GCP). * Deep background with integrations ...

Octave

Sr. Data Engineer

Denver, CO · On-site

$117K - $141K/yr

Job Summary: We're looking for a Sr. Data Engineer with strong data platform experience to help evolve our modern data stack and contribute to the foundation of our emerging AI and ML platform. This ...

Snowflake

Sr. Enterprise Data & AI Architect

Denver, CO · On-site

$69.25 - $92.75/hr

SQL mastery, Python/data engineering, and familiarity with the modern data stack. • Experience in competitive enterprise selling, including platform displacement or co‑existence. • Expertise in ...

Stio

Data Analyst

Denver, CO · Remote

This is a full-stack, horizontal role: the work spans data infrastructure (ingestion, modeling, transformation) through analysis, BI development, and direct stakeholder partnership across Finance ...

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Data Stacks information

What are Data Stacks?

Data stacks refer to the combination of tools, technologies, and frameworks used to collect, store, process, and analyze data within an organization. A typical data stack might include data ingestion tools, databases, data warehouses, processing frameworks, and analytics platforms. The purpose of a data stack is to streamline the flow of data from its source to actionable insights, supporting business intelligence and decision-making. Common examples include the Modern Data Stack, which often uses tools like Fivetran, Snowflake, dbt, and Looker.

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

To thrive as a Data Engineer, you need strong skills in database design, data modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Familiarity with tools such as SQL, Apache Spark, Hadoop, and cloud platforms like AWS or Google Cloud, as well as certifications in these technologies, is highly valued. Problem-solving abilities, attention to detail, and effective communication are important soft skills for this role. These skills are crucial for building reliable data pipelines, ensuring data quality, and supporting data-driven decision-making within organizations.

What is the difference between Data Stacks vs Data Analysts?

AspectData StacksData Analysts
Required CredentialsBachelor's in Computer Science, Data Science, or related fields; certifications like SQL, Python, or cloud platformsBachelor's in Statistics, Mathematics, or related fields; often certifications in Excel, SQL, or data visualization tools
Work EnvironmentTechnical teams, data engineering, software development environmentsBusiness units, reporting teams, data visualization platforms
Employer & Industry UsageTech companies, data-driven organizations, startupsFinance, marketing, healthcare, consulting firms

Data Stacks focus on building and managing the underlying data infrastructure, while Data Analysts interpret data to provide insights. Both roles require analytical skills, but Data Stacks professionals are more technical, working with data pipelines and databases, whereas Data Analysts focus on analyzing data to support decision-making.

What are some common challenges faced when managing modern data stacks, and how can they be addressed in this role?

Professionals managing modern data stacks often encounter challenges such as integrating diverse data sources, ensuring data quality, and maintaining system scalability as data volumes grow. Addressing these challenges typically involves collaborating closely with data engineers, analysts, and IT teams to implement robust data pipelines, automate data validation, and monitor system performance. Staying updated with evolving technologies and best practices is also crucial for proactive problem-solving and optimizing the data stack for business needs.
Data Stacks jobs near you
Infographic showing various Data Stacks job openings in Colorado as of June 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 70% In-person, 10% Hybrid, and 20% Remote job distribution.
Data Warehousing Specialist

Data Warehousing Specialist

Agelix Consulting

Lakewood, CO • On-site

Full-time

Posted 9 days ago

Job description

Job Summary for Senior Spatial Data Warehousing Specialist
- Lead the design, development, and implementation of data warehouses and data lakes, including geospatial and alphanumeric data.
- Integrate, consolidate, and geospatially enable data to support mapping, reporting, geospatial analysis, and self-service business intelligence (BI) needs.
- Utilize a variety of data warehousing tools and techniques, including traditional and modern data stack approaches, specifically for spatial data.
- Collaborate with project team members and leadership through effective task planning, project management, and coordination.
- Develop proof of concept and prototype reports, dashboards, and maps to help users visualize and analyze warehouse data.
- Support end users in mapping, reporting, and BI activities by publishing and maintaining accessible and reliable data sources.
- Apply advanced data analysis and data presentation skills to demonstrate the business value of spatial data environments.
- Bring at least 5 years of experience in building data warehouses (with spatial data) and developing data visualizations such as dashboards, reports, and maps.