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Snowflake Jobs in Colorado (NOW HIRING)

ClifyX

Data Engineer

Denver, CO · On-site

$117K - $141K/yr

ClifyX is seeking a Data Engineer with hands-on experience in Snowflake and Python. This critical onsite role requires the candidate to work from the Denver, CO office starting Day 1. Qualifications

Georgia IT, Inc.

Data Engineer - Denver, CO

Denver, CO · On-site

$117K - $141K/yr

The role involves working with Python, Cloud Data engineering, and ETL processes using tools such as Data Bricks, Snowflake, and Azure. Qualifications : Required : • Python • Cloud Data ...

fotf

Sr. Data Engineer, Data Products

Colorado Springs, CO · On-site

$113K - $135K/yr

Designs and builds Snowflake-centric solutions -- including optimized views, data models, and stored procedures -- that support business intelligence, analytics, business operations, and data quality.

fotf

Sr. Data Engineer, Data Products

Colorado Springs, CO · On-site

$113K - $135K/yr

Designs and builds Snowflake-centric solutions -- including optimized views, data models, and stored procedures -- that support business intelligence, analytics, business operations, and data quality.

Tech Mahindra

Senior Software Engineer - Data

Denver, CO · On-site

$110 - $115/hr

Snowflake Iceberg migration and table conversion activities, including SQL execution and data validation * AWS data pipeline development, monitoring, and production support across Glue, EMR/EMR ...

Apetan Consulting llc

Business (Data) Analyst

Denver, CO · On-site

$80 - $150/hr

SQL, SNOWFLAKE, DATABRICKS, AWS, REDSHIFT, DATA WAREHOUSE, ETL * Experience: 7 + years * Develop Data Solutions: Analyze, design, and build applications and data pipelines using AWS, Databricks ...

Capital Rx

Platform Developer, Operations

Denver, CO · On-site

Maintain and enhance Snowflake-related CI/CD processes, including developing and supporting GoCD pipelines, troubleshooting deployment issues, resolving Terraform failures, and addressing ...

Connect for Health Colorado

AI Developer/Engineer

Denver, CO · On-site +1

$111K - $145K/yr

Use Snowflake (including Snowflake Cortex where appropriate) to support AI/ML workloads, data preparation, and secure data access patterns. * Leverage Amazon Q (as applicable) and related enterprise ...

Capital Rx

Data Engineer II

Denver, CO · On-site

$108K - $136K/yr

Build, test, and document Snowflake data models and business logic in dbt * Apply and improve data quality, testing, observability, and lineage standards * Collaborate with cross-functional partners ...

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How much do snowflake jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for snowflake in Colorado is $71.09, according to ZipRecruiter salary data. Most workers in this role earn between $62.93 and $80.62 per hour, depending on experience, location, and employer.

What is a Snowflake?

A Snowflake job typically refers to tasks executed within Snowflake, a cloud-based data platform. These jobs can include data loading, transformation, querying, or scheduled tasks using Snowflake's task and stream features. They help automate data workflows, improve performance, and ensure efficient data management within the Snowflake ecosystem.

What are the key skills and qualifications needed to thrive in the Snowflake position?

To thrive as a Snowflake professional (such as a Snowflake Data Engineer or Administrator), you need a solid understanding of cloud data warehousing, SQL, and data modeling, typically supported by a degree in computer science or related fields. Experience with the Snowflake platform, data integration tools (like Informatica or Talend), and relevant certifications such as SnowPro are highly valuable. Strong problem-solving abilities, communication skills, and adaptability help professionals translate business requirements into data solutions and work effectively with cross-functional teams. These competencies are crucial for optimizing data workflows, ensuring system performance, and supporting the data-driven goals of an organization.

What are some common challenges faced by Snowflake professionals, and how can they be addressed?

Snowflake professionals often encounter challenges such as optimizing query performance, managing data security and access controls, and integrating Snowflake with multiple data sources. Addressing these challenges requires continuous learning about the platform’s evolving features, proactively monitoring query and storage usage, and collaborating closely with data architects, DevOps, and IT security teams. Staying up to date with best practices and regularly attending Snowflake community webinars or training can also be extremely helpful. Most companies encourage knowledge sharing and collaboration, so being proactive in problem-solving will help you thrive in this role.

Does Snowflake offer remote jobs?

Snowflake offers remote job opportunities for various roles, including data engineers, analysts, and software engineers. Many positions are fully remote or have flexible work arrangements, often requiring proficiency with cloud platforms and collaboration tools. Candidates should review specific job listings for location and remote work options.

Is Snowflake a good career?

A career as a Snowflake professional typically involves working with cloud data platforms, data warehousing, and SQL skills. It offers opportunities in data engineering, analytics, and cloud computing, with demand driven by the growth of data-driven decision making. Certifications and continuous learning can enhance job prospects in this field.

What exactly does Snowflake do?

A Snowflake professional typically works with the Snowflake data platform, which is a cloud-based data warehousing service. They manage data integration, optimize queries, and ensure data security within the platform, often using SQL and cloud infrastructure skills. The role involves supporting data analytics and business intelligence initiatives.

What are the most commonly searched types of Snowflake jobs in Colorado?

The most popular types of Snowflake jobs in Colorado are:

What are popular job titles related to Snowflake jobs in Colorado?

For Snowflake jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Snowflake jobs in Colorado look for?

The top searched job categories for Snowflake jobs in Colorado are:

What cities in Colorado are hiring for Snowflake jobs?

Cities in Colorado with the most Snowflake job openings:

Snowflake jobs near you
Infographic showing various Snowflake job openings in Colorado as of August 2026, with employment types broken down into 51% Full Time, and 49% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $147,865 per year, or $71.1 per hour.

AI Data Engineer | Information Technology

KSL Capital Partners

Denver, CO • On-site

$118K - $141K/yr

Full-time

Re-posted 3 days ago

Job description

KSL Capital Partners - Information Technology - AI Data Engineer - Denver, CO
Description
KSL Capital Partners, LLC ("KSL") is a leading global private equity firm specializing in travel and leisure enterprises. KSL specializes in investments across five primary sectors: hospitality, recreation, clubs, real estate, and travel services. KSL has approximately $25 billion of assets under management across its equity, debt, and tactical opportunities funds and has completed over 185 investments since 2005. These investments include some of the premier businesses and properties in travel and leisure globally. Today, KSL has offices in Denver, Colorado; Stamford, Connecticut; New York City, New York; and London, England.
To learn more, please visit https://kslcapital.com/.
Role
To support KSL's continued growth and evolving data and AI strategy, the Data & AI team is seeking an AI Data Engineer to build, scale, and maintain the firm's data infrastructure, with a specific mandate to prepare, structure, and pipeline data for AI and GenAI-driven data products. Reporting directly to the Data Architect, this role is responsible for the technical execution of KSL's data roadmap. This new hire will be the primary "builder" responsible for developing the pipelines and integrations that unify disparate data sources, both structured and unstructured, into a cohesive Snowflake environment, enabling reliable data flow and AI-native data products for FP&A, Deal Teams, and Portfolio Companies.
Working in close coordination with the Data Architect and a dedicated team of external consultants, this position is a hands-on technical role focused on the construction and operational excellence of our data ecosystem, spanning both traditional structured data pipelines and the infrastructure required to power AI and GenAI applications. The ideal candidate is a highly productive engineer who brings a "reliability-first" mindset to data modeling and pipeline development, along with genuine experience preparing data for AI/ML consumption. As a foundational hire on a scaling team, you will embrace modern AI-assisted development tools to work efficiently and support the transition of data warehouse ownership in-house.
Responsibilities
  • Build and monitor robust ETL/ELT pipelines that ingest and transform data from portfolio companies, property management systems, ERPs, and SaaS platforms (Juniper Square, Maybern, Workiva) into Snowflake
  • Execute data modeling tasks in Snowflake to create clean, well-modeled, and performant datasets that power self-serve analytics and dashboards in Sigma and Workiva, as well as direct consumption by Claude, ChatGPT, and AI agents for querying, reporting, and automated workflows
  • Design and build ingestion pipelines for unstructured and semi-structured data (offering memoranda, DDQs, LP agreements, and other deal and portfolio documents stored in Box), parsing and structuring content to support retrieval-augmented generation (RAG) and AI-assisted analysis
  • Build and maintain embedding and vector infrastructure, primarily leveraging Snowflake Cortex Search and native vector data types, to enable governed, high-quality retrieval for Claude and other AI applications querying KSL's data
  • Partner with the Data Architect to extend Snowflake's data model to support AI-specific consumption patterns, including metadata tagging, lineage tracking, and access controls appropriate for AI-driven queries and agents
  • Support the technical onboarding of new investments, assisting with source-to-target mapping, API integrations, and validation of data quality from day one
  • Implement data quality checks and anomaly detection within the pipeline to ensure the "Golden Record" remains the trusted source of truth for both traditional reporting and AI-driven data products
  • Collaborate daily with the Data Architect to translate architectural blueprints into functional, maintainable code and automated workflows, including the integration of AI/agentic tooling (e.g., MCP connections) with Snowflake and other core platforms

Education and Experience
  • Bachelor's Degree in Computer Science, Information Systems, Data Engineering, or a related technical field; degrees in Finance, Economics, or Accounting combined with strong technical experience will also be considered
  • 5+ years in data engineering, data architecture, or a related technical role, with at least some experience in a private equity, investment management, or financial services setting; experience building data pipelines for AI/ML or GenAI applications is a strong differentiator

Desired Skills
Snowflake & Cloud Data Platform
  • Strong proficiency in Snowflake core features (Tasks, Streams, Dynamic Tables) and experience using Snowpark (Python) for complex in-warehouse transformations
  • Deep expertise in SQL and dbt (data build tool) for modular, version-controlled data modeling
  • Demonstrated experience with system connectivity and API-based integrations, connecting third-party platforms (PMS, accounting software, CRMs, data feeds) to a central data warehouse via REST APIs, SFTP pipelines, or native connectors (e.g., Fivetran, dbt, or custom ETL); ability to troubleshoot and maintain data pipelines end-to-end

AI & GenAI Data Infrastructure
  • Experience building data pipelines that support AI/ML or GenAI applications, including handling unstructured data (documents, PDFs, text) and preparing it for retrieval or model consumption
  • Familiarity with vector databases and embedding infrastructure (Snowflake Cortex Search or native vector data types preferred given KSL's platform); general vector database experience (Pinecone, Weaviate, or similar) a plus
  • Working understanding of retrieval-augmented generation (RAG) pipeline design and the data requirements of LLM-based applications
  • Exposure to MCP (Model Context Protocol) or similar tool-calling/agentic integration patterns a plus

Modeling & Analytics Enablement
  • Proven ability to organize data from multiple sources into a unified reporting layer, making it easy for business users to get the answers they need without navigating complex underlying systems
  • Familiarity with accounting and finance fundamentals (e.g., financial statements, key performance metrics, capital structures) is a plus, since KSL's data consumers are primarily finance and investment teams, and an ability to speak their language accelerates collaboration
  • Experience with BI and reporting tools (Sigma, Workiva, Power BI, or similar), with an eye for translating business questions into clear, actionable visualizations

Communication & Collaboration
  • Exceptional verbal, written and listening communication skills
  • Strong project management skills, with a demonstrated ability to work effectively across functions, manage competing priorities independently, and translate technical concepts for non-technical stakeholders
  • Ability to operate both strategically and tactically, comfortable diving into the details to solve problems while also planning for long-term growth
  • Excellent operational, organizational and follow-up skills with the ability to manage and process complex operational work
  • Strong problem-solving and data analytical skills, including the ability to work with large datasets, frame and breakdown problems, and synthesize themes and insights from analyses; problem solving includes both quantitative and qualitative information and problems
  • Ability to multitask and prioritize without feeling overwhelmed and quickly pivot from one task to another

The above statements are intended to describe the general nature and level of work performed by employees assigned to this classification. The statements are not intended to be an exhaustive list of all job duties performed by employees assigned to this classification.

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