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Data Analytics Engineer Jobs in Colorado (NOW HIRING)

CoorsTek, Inc.

Forward Deployed Data Engineer

Golden, CO · On-site

$118K - $142K/yr

Identify high-value opportunities for data, analytics, AI, or workflow enablement by partnering with plant leaders, engineers, quality, supply chain, maintenance, finance, and business leaders

CoorsTek

Forward Deployed Data Engineer

Golden, CO

$118K - $142K/yr

Identify high-value opportunities for data, analytics, AI, or workflow enablement by partnering with plant leaders, engineers, quality, supply chain, maintenance, finance, and business leaders.

Cymertek

Cloud Big Data Software Engineer

Aurora, CO · On-site

$56.75 - $75.25/hr

Cloud Big Data Software Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note ... Familiarity with real-time analytics platforms * Knowledge of Infrastructure as Code (IaC) tools ...

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All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Colorado

Data Analytics Engineer information

See Colorado salary details

$46.8K

$136.4K

$186.6K

How much do data analytics engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for data analytics engineer in Colorado is $136,399.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,400.00 and $144,600.00 per year, depending on experience, location, and employer.

How do Data Analytics Engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

Can a data engineer make 200k?

Data engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and those in high-demand markets more likely to reach or exceed this level.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, machine learning, and proficiency with tools like Python, SQL, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes equity compensation.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

Is 40 too late for data science?

Data Analytics Engineers and data science professionals can successfully transition into the field at age 40 or older, as skills such as programming, statistical analysis, and experience with tools like Python or SQL are valuable regardless of age. Many employers value diverse experience and lifelong learning, and certifications or online courses can help enhance credentials at any age.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and systems to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to deliver actionable insights.
What are the most commonly searched types of Data Analytics Engineer jobs in Colorado? The most popular types of Data Analytics Engineer jobs in Colorado are:
What are popular job titles related to Data Analytics Engineer jobs in Colorado? For Data Analytics Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Data Analytics Engineer jobs in Colorado look for? The top searched job categories for Data Analytics Engineer jobs in Colorado are:
What cities in Colorado are hiring for Data Analytics Engineer jobs? Cities in Colorado with the most Data Analytics Engineer job openings:
Data Analytics Engineer jobs near you
Infographic showing various Data Analytics Engineer job openings in Colorado as of July 2026, with employment types broken down into 1% Internship, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution, with an average salary of $136,399 per year, or $65.6 per hour.
Forward Deployed Data Engineer

Forward Deployed Data Engineer

CoorsTek, Inc.

Golden, CO • On-site

$118K - $142K/yr

Full-time

Re-posted 12 days ago

CoorsTek rating

8.1

Company rating: 8.1 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

Job description

It's exciting to work for a company that makes the world measurably better.
We're committed to bringing safety, quality, and customer focus to the business of advanced ceramics manufacturing.
Job Title
Forward Deployed Data Engineer
Forward Deployed Data Engineer works to understand workflows, data sources, data meaning, and decision needs, then translate those needs into governed Databricks data products, reusable data models, analytics, and AI-enabled solutions.
This role reports to a leader in engineering team and works closely with IT, including Data & Analytics, Manufacturing IT/OT, Enterprise Applications, Cybersecurity, and Architecture. The Forward Deployed Data Engineer bridges plant operations, business leadership, and IT to improve enterprise insight while preserving appropriate plant-level flexibility.
The role supports manufacturing data strategy by aligning plant data, ETL/ELT[RD1.1][DT1.2], data hierarchy, , metrics, and semantic definitions so plant teams and central leadership can make, faster, trusted data driven decisions.
Roles and Responsibilities
  • Understand workflows, constraints, decision points, and data needs embed with manufacturing sites, business units, and functional teams.
  • Identify high-value opportunities for data, analytics, AI, or workflow enablement by partnering with plant leaders, engineers, quality, supply chain, maintenance, finance, and business leaders .
  • Assess manufacturing data alignment across SAP, QAD, Apriso, Ignition, InfinityQS, LIMS, CMMS, equipment data, spreadsheets, databases, and other sources at a plant by plant level.
  • Translate ambiguous business and manufacturing problems into practical data requirements, data products, analytics, applications, and implementation plans.
  • Define mappings, data definitions, transformation rules, business logic, data quality rules, and metric calculations for trusted manufacturing insights.
  • Help establish an aligned manufacturing data hierarchy across sites, equipment, work centers, operations, products, materials, orders, quality events, and maintenance events.
  • Develop and/or support Databricks-based data products, pipelines, notebooks, dashboards, models, and applications using approved architecture and governance patterns.
  • Partner with IT Data & Analytics on ETL/ELT patterns using Databricks, Delta Lake, Unity Catalog, workflows, governed tables, semantic definitions, and reusable data assets.
  • Balance local plant flexibility with enterprise standardization by defining what should be harmonized centrally and what plant variation should be preserved.
  • Improve data capture, completeness, quality, and ownership where source data is inconsistent, manual, incomplete, or not decision-ready.
  • Create minimum viable data products with real users, then mature successful solutions into governed, supportable production patterns, including Databricks-hosted applications.
  • Partner with IT architecture, cybersecurity, enterprise applications, integration, infrastructure, and manufacturing IT/OT to meet standards for identity, access, lineage, logging, supportability, resiliency, and responsible AI usage.
  • Document lineage, transformation logic, business definitions, solution designs, runbooks, ownership models, and reusable patterns that can scale across plants and business units.
  • Coach plant engineers, analysts, and business users on data definitions, data quality, Databricks workflows, analytics adoption, and responsible AI-enabled capabilities.
  • Serve as a point of contact for feedback loop between the business and IT by identifying recurring plant needs, architecture gaps, and reusable platform improvements.

Job Requirements
Education
  • Bachelor's degree in Engineering, Industrial Engineering, Manufacturing Systems, Data Analytics, Computer Science, Information Technology, or a related field required.
  • Master's degree preferred.
Experience
  • 5 or more years of progressive experience in data engineering, analytics engineering, manufacturing systems, industrial technology, enterprise analytics, operational excellence, or a related field.
  • 3 or more years working with manufacturing, plant operations, quality, supply chain, maintenance, engineering, or industrial data environments preferred.
  • Experience translating operational workflows into practical data, analytics, dashboard, pipeline, or application solutions.
  • Experience with Databricks, Delta Lake, lakehouse architecture, SQL, Python, PySpark, data modeling, ETL/ELT, or modern data engineering practices .
  • Preferred experience with manufacturing systems such as SAP, QAD, MES, Apriso, Ignition, InfinityQS, LIMS, CMMS, SCADA, historians, or equipment data sources.
  • Preferred experience across multi-site or global manufacturing environments and influencing outcomes without direct authority.
Functional / Technical Knowledge, Skills & Abilities
  • Strong ability to bridge plant operations, business leadership, and IT by translating manufacturing problems into data, analytics, application, and architecture requirements.
  • Strong understanding of manufacturing performance concepts such as yield, scrap, rework, throughput, cycle time, downtime, quality events, maintenance events, OEE, inventory, and production scheduling.
  • Strong working knowledge of data modeling, transformation, quality, semantic layers, metric definitions, metadata, lineage, and data governance.
  • Working knowledge of Databricks capabilities, including Delta tables, notebooks, workflows/jobs, SQL, Unity Catalog, data lineage, and governed analytical access patterns.
  • Ability to write and review SQL and Python-based data transformation logic; PySpark experience preferred.
  • Ability to define practical data hierarchies and translation layers that support local operational needs while enabling enterprise reporting and leadership insight.
  • Ability to develop prototypes, MVPs, dashboards, data products, and Databricks-enabled applications that validate value quickly and improve iteratively.
  • Ability to partner effectively with IT teams on architecture, cybersecurity, integration, enterprise applications, infrastructure, support, and lifecycle expectations.
  • Strong communication and documentation skills, including data dictionaries, mapping documents, process flows, business logic definitions, architecture notes, testing evidence, and runbooks.
  • Ability to manage multiple initiatives, prioritize by business value, work in ambiguity, and travel frequently for plant-facing data alignment and enablement.
Preferred Certifications
  • Relevant Databricks certifications, including Data Engineer, Data Analyst, Machine Learning, or Lakehouse Fundamentals preferred.
  • Relevant Microsoft Azure, Power BI, data engineering, analytics, AI, or cloud certifications preferred.
  • Lean Six Sigma, operational excellence, manufacturing systems, ISA-95, APICS, or related industrial operations certifications are a plus.

Target Hiring Range
Annual Salary: USD 115,000.00 - USD 155,000.00
Actual compensation is commensurate with experience, skills and education. CoorsTek strives to give all qualified applicants equal opportunity and to make selection decisions on job related factors. Do not provide any information on the application which will indicate your race, color, religion, national origin, sex, age, disability, sexual orientation, gender identity, pregnancy, genetic information, veteran status, or any other status protected by law or regulation.
If you like working for a company that makes a real difference in the world, you'll enjoy your career with us!

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