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Remote Data Engineer Jobs in Highlands Ranch, CO

KORE1 Technologies

Head of Data Platform

Denver, CO · Remote

... remote. Why This Role Exists We operate a large-scale, multi-tenant SaaS platform supporting ... These systems rely on scalable feature engineering, real-time data pipelines, model infrastructure ...

Owens & Minor

Senior Manager, Data Engineering

Denver, CO · On-site +1

$140K - $155K/yr

The role is fully remote. Applicants in different states are encouraged to apply. Key Responsibilities Leadership & Team Management - Lead, mentor, and develop a team of data engineers and BI ...

NuView Analytics

Data Analyst (Remote)

Denver, CO · Remote

$80K - $100K/yr

Salary: $80k100K + bonus + benefits Location: 100% remote for US-based candidates Responsibilities: * Candidate will complete data analytics and data science projects for clients * Candidate will ...

Eliassen Group

Data Analyst

Greenwood Village, CO · Remote

$60 - $70/hr

Hybrid 4 days onsite, 1 remote. in Greenwood Village, CO Our client seeks experienced Data Analysts ... Perform code reviews with other developers. * Collaborate with other members of the team.

Prologis

Program Director, Data & Analytics

Denver, CO · On-site +1

You will connect strategy to execution across Data Engineering, Analytics Engineering, and Data ... remote teams * Strong change management mindset and comfort operating in evolving environments

Invoca

Senior ML Engineer

Denver, CO · On-site +1

$107K - $147K/yr

About the Team The Data Platform team owns the full ML lifecycle at Invoca, from model training and ... Familiarity with RLHF or preference training is a bonus 📍 Location This is a remote-first role.

JLL

Senior Mechanical Commissioning Engineer (REMOTE)

Denver, CO · On-site +1

$107K - $142K/yr

DATA CENTERS & MISSION CRITICAL PROJECTS This position can be remote (work from home) but must live ... Directing cross-functional commissioning teams of 2-8+ engineers and technicians while coordinating ...

Career TEAM

Data Conversion Software Engineer

Golden, CO · Remote

$60K - $100K/yr

As a Data Conversion Software Engineer , you'll help design, build, and maintain systems that transform and integrate data across platforms supporting government-funded workforce development programs ...

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All JobsRemote Data Engineer JobsRemote Data Engineer Jobs in Highlands Ranch, CO

Remote Data Engineer information

See Highlands Ranch, CO salary details

$46.7K

$136.2K

$186.3K

How much do remote data engineer jobs pay per year?

As of Jul 5, 2026, the average yearly pay for remote data engineer in Highlands Ranch, CO is $136,152.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,200.00 and $144,300.00 per year, depending on experience, location, and employer.

What Does a Remote Data Engineer Do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

What is the difference between Remote Data Engineer vs Remote Data Analyst?

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

How do remote Data Engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

What is a Remote Data Engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

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

To thrive as a Remote Data Engineer, you need strong programming skills in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.
More about Remote Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in Highlands Ranch, CO? The most popular types of Data Engineer jobs in Highlands Ranch, CO are:
What are popular job titles related to Remote Data Engineer jobs in Highlands Ranch, CO? For Remote Data Engineer jobs in Highlands Ranch, CO, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineer jobs in Highlands Ranch, CO look for? The top searched job categories for Remote Data Engineer jobs in Highlands Ranch, CO are:
What cities near Highlands Ranch, CO are hiring for Remote Data Engineer jobs? Cities near Highlands Ranch, CO with the most Remote Data Engineer job openings:
Remote Data Engineer jobs near you
Head of Data Platform

Head of Data Platform

KORE1 Technologies

Denver, CO • Remote

Contractor

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Job description


KORE1, a nationwide provider of staffing and recruiting solutions, has an immediate opening for a Head of Data Platform that is fully remote. 

Why This Role Exists
We operate a large-scale, multi-tenant SaaS platform supporting thousands of enterprise customers nationwide. Our data ecosystem - spanning relational databases, NoSQL systems, streaming events, and cloud-based data lakes - powers complex transactional workflows, integrations, analytics, and operational decision-making at scale.

As the platform evolves, we are building intelligent, closed-loop optimization systems capable of observing operational signals, predicting outcomes, automating decisions, and continuously learning from results. These systems rely on scalable feature engineering, real-time data pipelines, model infrastructure, telemetry, and strong governance controls.

This role will own the foundational data architecture that enables those capabilities. You will lead the design of the data platform, feature infrastructure, governance framework, and real-time data systems that transform a transactional SaaS platform into an intelligent decision engine.
This is a highly hands-on leadership role focused on modern data architecture, AI/ML infrastructure, streaming systems, governance, and scalable platform engineering.
Scope & Scale
  • Large-scale multi-tenant SaaS environment supporting thousands of enterprise customers
  • High-volume transactional and operational data workloads
  • Complex third-party integrations spanning multiple data formats and protocols
  • Real-time streaming systems and event-driven architectures
  • Multiple optimization and intelligent automation initiatives requiring scalable feature engineering and telemetry systems
What You Will OwnData Platform Architecture
  • Design and own the end-to-end data platform architecture including raw ingestion, canonical entity modeling, analytics layers, feature infrastructure, and telemetry systems.
  • Build scalable frameworks for feature engineering, data quality, lineage, governance, and operational reliability.
  • Define patterns for tenant isolation, auditability, retention policies, and secure data access at scale.
Feature Store & AI Data Infrastructure
  • Lead the design and operation of online and offline feature infrastructure supporting real-time scoring and model training workflows.
  • Establish standards for feature ownership, freshness SLAs, training/inference parity, metadata governance, and lifecycle management.
  • Build scalable pipelines supporting ML models, intelligent automation workflows, and AI-enabled platform capabilities.
Streaming & Event-Driven Systems
  • Design and operate real-time streaming pipelines, event-driven data propagation, and change-data-capture systems.
  • Support low-latency feature materialization and telemetry processing across distributed services.
  • Ensure scalability, observability, and reliability across streaming infrastructure.
Data Governance & Quality
  • Establish enterprise-grade governance frameworks covering PII handling, tenant isolation, retention policies, audit logging, and cost attribution.
  • Implement automated monitoring for schema drift, stale pipelines, null spikes, feature skew, and data inconsistencies.
  • Own data quality standards and operational accountability across the platform.
Platform Modernization & Migration Strategy
  • Lead data migration and modernization initiatives across relational and NoSQL systems.
  • Define scalable migration patterns including dual-write validation, reconciliation strategies, and zero-downtime cutovers.
  • Partner with Engineering, Infrastructure, Product, and AI teams to align platform evolution with business goals.
Technical Leadership
  • Mentor engineers and data practitioners across multiple teams.
  • Drive architecture reviews, data modeling standards, and platform engineering best practices.
  • Establish scalable operating mechanisms and technical governance processes.
Technical EnvironmentData Platforms & Storage
  • Relational and NoSQL systems including Aurora/MySQL/PostgreSQL, DynamoDB, S3 data lakes, and distributed storage architectures
  • Modern lakehouse and analytical storage patterns
Streaming & Event Systems
  • Event-driven architectures, streaming pipelines, CDC frameworks, and real-time feature propagation systems
AI & ML Infrastructure
  • Feature stores, model training pipelines, model lifecycle infrastructure, and AI-enabled workflow systems
  • Production AI/ML deployment and observability frameworks
Data Engineering & Analytics
  • ETL/ELT orchestration platforms
  • Distributed analytics environments and BI tooling
  • Metadata cataloging, governance, and observability systems
Infrastructure & DevOps
  • AWS cloud infrastructure, infrastructure-as-code, CI/CD, monitoring, and operational tooling
Hands-On Expectations
This is not a purely strategic leadership role. The expectation is a strong balance of:
  • hands-on engineering and SQL/data work
  • architecture and systems design
  • technical mentorship and cross-functional leadership
You should be comfortable operating both as a high-level architect and as a deeply technical contributor on critical systems and pipelines.
First 12 MonthsMonths 1-3
  • Evaluate the existing data landscape, integrations, pipelines, and governance gaps
  • Define canonical entity models and future-state data architecture standards
  • Publish initial architecture recommendations and modernization priorities
Months 4-6
  • Establish foundational feature infrastructure and governance frameworks
  • Deliver initial modernization and migration initiatives
  • Implement automated monitoring and data quality controls
Months 7-9
  • Support production deployment of optimization and intelligent automation workflows
  • Operationalize feature lifecycle management, telemetry systems, and model infrastructure
  • Expand streaming and event-driven capabilities across the platform
Months 10-12
  • Deliver additional production-scale optimization and AI-enabled data capabilities
  • Mature governance, observability, and platform reliability standards
  • Define long-term roadmap for data platform scalability and intelligent systems evolution
RequirementsRequired Qualifications
  • 7+ years of experience in data engineering, platform engineering, or data architecture roles
  • Experience operating at a senior architect, principal, or platform leadership level
  • Deep expertise in both relational and NoSQL data modeling and distributed data systems
  • Strong experience building scalable feature infrastructure and real-time data platforms
  • Hands-on experience with cloud-native AWS data and analytics services
  • Experience supporting AI/ML workflows, feature engineering, or production AI systems
  • Strong understanding of event-driven architectures, CDC, and streaming data systems
  • Experience with large-scale multi-tenant platform architectures and governance challenges
  • Strong data governance instincts around security, auditability, PII handling, and operational accountability
  • Ability to balance architecture leadership with hands-on implementation work
Strongly Preferred
  • Experience supporting AI/ML lifecycle infrastructure including feature stores, model registries, monitoring, and production deployment workflows
  • Experience with LLM-related infrastructure, embeddings pipelines, retrieval systems, or intelligent automation workflows
  • Experience building closed-loop analytics or optimization systems with telemetry and outcome tracking
  • Strong experience with data quality monitoring and anomaly detection at scale
  • Familiarity with lakehouse architectures, open table formats, and large-scale analytical systems
Nice to Have
  • Experience in SaaS, fintech, automotive, marketplace, or transaction-heavy industries
  • Familiarity with complex third-party integrations and heterogeneous data sources
  • Experience with vector databases or semantic retrieval systems
  • Exposure to optimization, recommendation, scheduling, or operational intelligence systems
Benefits & Culture
We are a fast-paced and collaborative technology organization focused on building scalable platforms that improve operational efficiency, intelligent automation, and customer outcomes.
We offer:
  • Comprehensive medical, dental, and vision coverage
  • Employer-sponsored disability and life insurance
  • 401(k) with company match
  • Generous paid time off and company holidays
  • High-impact ownership over foundational AI and data platform initiatives
  • Opportunity to shape next-generation intelligent systems at scale




Compensation depends on experience but is typically 160k-195k

ABOUT KORE1
Specializing in professional and technical recruiting, KORE1 is committed to supporting top IT, Engineering, Creative, Scientific, Accounting and Finance professionals in their career paths. We build deep relationships with leading companies, connecting them to exceptional talent every day. With extensive industry expertise and unmatched opportunities, our goal is to provide a unique experience for our contractors and consultants as they prepare for their next role. We are passionate about matching the right people with the right companies.

Kore1 provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Kore1 complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. Kore1 expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of Kore1's employees to perform their job duties may result in discipline up to and including discharge.
Education:Employment Type: CONTRACTOR

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