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Remote Data Engineer Jobs in Chaska, MN (NOW HIRING)

Thrivent Financial

Senior Engineer

Minneapolis, MN · On-site +1

$157K/yr

Use data to measure progress; * Promote and expand on the use of the CI/CD pipeline to improve the ... Coach Engineers; * Provide guidance to junior engineers to help them learn foundational software ...

Polaris, Inc.

Product Manager (Data Science)

Medina, MN · On-site +1

$140K - $160K/yr

Working in a highly cross-functional model, you will partner with engineering, architecture, and ... Ability to work in a remote or hybrid model while being commutable to Medina, MN for quarterly ...

Syscom, Inc.

Azure Database Engineer

Saint Paul, MN · On-site +1

$55.50 - $69/hr

Looking for your next Azure cloud data engineering challenge? If you're an experienced Database ... Remote/Hybrid. Candidates should be available to work onsite in St. Paul, MN, as needed for ...

Thrivent Financial

Senior Engineer (e-MG)

Minneapolis, MN · On-site +1

$127K - $168K/yr

Use data to measure progress; Promote and expand on the use of the CI/CD pipeline to improve the deployment and build process; Participate in team support rotation and provide expert knowledge on ...

New

Centstone

Database Developer

Minneapolis, MN · Remote

Database Developer Location: Remote (Local to Minnesota Preferred) Employment Type: Contract ... Execute large-scale data migration, cleansing, validation, and transformation across enterprise ...

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All JobsData Engineer JobsRemote Data Engineer JobsRemote Data Engineer Jobs in Chaska, MN

Remote Data Engineer information

See Chaska, MN salary details

$47.7K

$139.1K

$190.3K

How much do remote data engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for remote data engineer in Chaska, MN is $139,084.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,800.00 and $147,400.00 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 cities near Chaska, MN are hiring for Remote Data Engineer jobs?

Cities near Chaska, MN with the most Remote Data Engineer job openings:

Remote Data Engineer jobs near you
Infographic showing various Remote Data Engineer job openings in Chaska, MN as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 15% Part Time, and 7% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $139,084 per year, or $66.9 per hour.

Senior AI Engineer - Agentic Systems & Data Pipelines

Collaboration.Ai

Minneapolis, MN • On-site, Remote

$110K - $150K/yr

Full-time

Posted 18 days ago

Job description

Who We Are
Collaboration.Ai is a mission-focused, AI-powered software and services company based in Minnesota, with employees, partners, and customers around the world. We unite people, technology, and purpose to accelerate breakthroughs that transform industries, empower communities, and create a more sustainable future. We collaborate with organizations across the defense ecosystem, helping them navigate complex challenges and drive transformative change.
Our Products
NetworkOS - NetworkOS is an AI-powered platform that aligns people, purpose, ideas, and expertise in real-time, generating actionable insights to propel movements forward.
CrowdVector - CrowdVector is an integrated solution marketplace and innovation management platform that rapidly uncovers new ideas and advances breakthroughs to fuel movements.
To learn more about us, visit collaboration.ai.
About the Role
You'll build the agentic systems and data pipelines behind NetworkOS's AI capabilities: production agent workflows built on industry-leading agent SDKs and harnesses, MCP servers, and Agent Skills standards; the eval and observability layer that keeps LLM quality measurable; and the ingestion pipelines that turn messy, diverse data sources into queryable knowledge.
This is an execution seat, not an ivory tower. You'll commit code every week, ship agents as product capability rather than demos, and help shape a roadmap that's heading deep into graph + agents territory - for customers in defense, healthcare, and regulated enterprise.
Agents in production. Pipelines that hold. Evals that keep everyone honest.
This opportunity is remote with a preference for candidates in the Twin Cities area (Minneapolis, Saint Paul); however all candidates are encouraged to apply!
What You'll Do
  • Ship production agent systems - design, build, and operate agentic workflows (agent SDKs, MCP servers, Agent Skills standards) powering AI-driven matching, analysis, and data intelligence
  • Operationalize LLM quality - build the eval and observability layer with Langfuse, golden datasets, LLM-as-judge patterns, and FinOps-style tracking so every workflow has measurable quality, cost, and latency
  • Engineer data pipelines - robust ingestion of documents, structured data, and external sources into searchable knowledge bases with quality validation, deduplication, and incremental updates
  • Own retrieval quality - hybrid search combining vector, keyword, and metadata retrieval, continuously improved through reranking, query expansion, and contextual compression
  • Accelerate with AI - build custom MCP tools and Agent Skills that make the whole engineering team measurably faster
  • Execute alongside the team - pair with full-stack engineers on AI integration points, contribute to incident response for AI services, and keep your hands in the code
Our Tech Stack
  • Languages: Python (primary); Kotlin (core platform language at CAI); TypeScript/Node.js and other modern languages (secondary)
  • AI/ML: FastAPI, Pydantic; multi-provider LLM SDKs (Anthropic, OpenAI, and others)
  • Agentic Tooling: Claude Code/Codex/etc.; industry-leading agent SDKs and harnesses; MCP servers; Agent Skills standards
  • LLM Operations: Langfuse + evals (golden datasets, LLM-as-judge); in-house FinOps tracking (token usage, latency, cost); multi-provider orchestration including AWS Bedrock
  • Search & Retrieval: Vector databases, OpenSearch, embedding models
  • Data: PostgreSQL, Amazon S3; streaming pipelines (Kafka/Kinesis) where needed
  • Infrastructure: Docker, Kubernetes (AWS EKS); DataDog + OpenTelemetry observability
What We're Looking For
Must Haves
  • 7+ years of professional software engineering experience, with 3+ years focused on AI/ML or data engineering
  • Production agentic/LLM application experience - built and operated systems around LLM APIs (Anthropic, OpenAI) serving real users: agents, tool-use, or orchestrated LLM workflows
  • Data engineering background - robust, scalable pipelines for AI/ML workloads
  • LLM operations experience - evals and observability for production LLM systems (quality, cost, latency)
  • Production retrieval experience - vector databases and/or search engines (OpenSearch, Elasticsearch)
  • Modern Python stack proficiency - FastAPI, Pydantic, async/await, modern dependency management
  • AI-native workflows - demonstrated ability to leverage Claude Code/Codex or similar agentic coding tools to accelerate development
  • Experience with Docker, Kubernetes, and AWS
  • US citizenship required (DoD contracting - IL4/IL5 environments - and FedRAMP compliance)
Nice-to-Haves
  • Deep agentic ecosystem experience - Agent Skills standards, custom MCP servers, agent SDKs across major vendors
  • Advanced RAG expertise - GraphRAG, agentic RAG, contextual retrieval, reranking strategies
  • Graph data experience - knowledge graphs, graph databases, or graph-based retrieval
  • Model selection & rightsizing - matching models to domain-specific use cases across quality, cost, and latency tradeoffs
  • Streaming data experience (Kafka, Kinesis) for real-time knowledge base updates
  • Research background, open-source contributions, or an advanced degree in ML/IR/NLP
Why Join Collaboration AI?
Real AI engineering, not a wrapper shop. Production agents, hybrid retrieval, continuous evals, and a roadmap heading into graph + agents - with the autonomy to shape how it's built.
AI-native by default. We build with AI, not just for AI. Agentic coding tools (Claude Code/Codex/etc.), agent SDKs and harnesses, MCP servers, and Agent Skills standards are how we work daily - you'll both use and build them.
Work that matters. Defense, healthcare, and regulated industries - SOC 2 and NIST compliance, FedRAMP readiness, and customers whose missions demand AI they can trust.
Small, senior team. Early-stage impact with your work visible from week one. You'll help set the bar for how AI engineering is done here.

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