ZipRecruiter

Log In

1

Weekend Amazon Data Engineer Jobs in Minneapolis, MN

Collaboration.Ai

Senior Software Engineer

Minneapolis, MN · On-site +1

$127K - $168K/yr

Engineer data pipelines - robust ingestion of documents, structured data, and external sources into ... Data: PostgreSQL, Amazon S3; streaming pipelines (Kafka/Kinesis) where needed * Infrastructure:

Amazon

Area Manager

Woodbury, MN · On-site

... Engineering, Loss Prevention, Quality Assurance, Human Resources to develop plans to meet business ... Amazon (blue badge/FTE) experience - Work a flexible schedule/shift/work area, including weekends ...

Amazon

EHS Specialist

Brooklyn Park, MN · On-site

Join Amazon's mission to become Earth's safest place to work. At Amazon, we've set the ambitious ... Safety Program Excellence & Implementation - Drive comprehensive safety programs through data ...

Amazon

EHS Specialist

Brooklyn Park, MN · On-site

Join Amazon's mission to become Earth's safest place to work. At Amazon, we've set the ambitious ... Safety Program Excellence & Implementation - Drive comprehensive safety programs through data ...

Amazon

Senior Operations Manager

Woodbury, MN · On-site

... Amazon's success which is built on a foundation of customer obsession, and innovation. This ... Engineering, Safety, IT and other leaders) to build and secure support and resources for projects ...

3M

Cryptographic Engineer

Maplewood, MN · On-site

$109K - $133K/yr

... data migrations: * Manage the Enterprise Secure Key Lifecycle (ESKM) platform from Utimaco ... Partner with cloud platform engineering teams in support of Amazon Certificate Manager (ACM), AWS ...

previous page

Showing results 41-60

All JobsAmazon Data Engineer JobsWeekend Amazon Data Engineer JobsWeekend Amazon Data Engineer Jobs in Minneapolis, MN

Weekend Amazon Data Engineer information

See Minneapolis, MN salary details

$46.4K

$135.4K

$185.3K

How much do weekend amazon data engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for weekend amazon data engineer in Minneapolis, MN is $135,398.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What is a Weekend Amazon Data Engineer?

Weekend Amazon Data Engineers are professionals who work with Amazon's data infrastructure, usually on a part-time or flexible basis during weekends. They are responsible for building, maintaining, and optimizing data pipelines and systems that support data analysis and business decision-making. Their work often involves using Amazon Web Services (AWS) tools, programming languages such as Python or SQL, and collaborating with data scientists or analysts. Weekend roles are ideal for those seeking supplementary income, work-life balance, or an opportunity to gain experience in cloud-based data engineering.

What does a typical weekend look like for a Weekend Amazon Data Engineer, and how does the work schedule differ from weekday roles?

As a Weekend Amazon Data Engineer, you can expect to focus on monitoring data pipelines, addressing urgent data-related issues, and supporting critical deployments that often occur during lower-traffic periods on weekends. This role may involve collaborating with on-call engineers, data analysts, and product teams to ensure data infrastructure stability and resolve incidents quickly. The weekend schedule typically allows for more independent work, but you will still participate in virtual stand-ups or handoff meetings with weekday teams to maintain continuity. Flexibility and strong communication are important, as you'll often be the primary point of contact for data engineering concerns during your shift.

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

To thrive as a Weekend Amazon Data Engineer, you need strong proficiency in data modeling, SQL, and programming languages such as Python or Java, often backed by a degree in computer science or a related field. Familiarity with AWS services (like Redshift, S3, and Glue), ETL tools, and data warehousing certifications is highly valuable. Excellent problem-solving skills, attention to detail, and effective collaboration are standout soft skills for this role. These competencies ensure the reliable and efficient processing of large datasets, supporting business needs even during off-peak times.

What is the difference between Weekend Amazon Data Engineer vs Weekend Amazon Data Analyst?

AspectWeekend Amazon Data EngineerWeekend Amazon Data Analyst
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentData pipelines, cloud platforms, ETL processesData interpretation, reporting, visualization tools
Employer & Industry UsageAmazon, e-commerce, cloud servicesAmazon, retail, marketing teams

Weekend Amazon Data Engineers focus on building and maintaining data infrastructure, while Data Analysts interpret data and generate reports. Both roles often work in the same environment but serve different functions within Amazon's data ecosystem.

What are the most commonly searched types of Amazon Data Engineer jobs in Minneapolis, MN?

The most popular types of Amazon Data Engineer jobs in Minneapolis, MN are:

What cities near Minneapolis, MN are hiring for Weekend Amazon Data Engineer jobs?

Cities near Minneapolis, MN with the most Weekend Amazon Data Engineer job openings:

Weekend Amazon Data Engineer jobs near you

Senior Software Engineer

Collaboration.Ai

Minneapolis, MN • On-site, Remote

$127K - $168K/yr

Full-time

Re-posted 6 days ago

Key responsibilities

  • Build, deploy, and operate production agent systems and workflows using agent SDKs, MCP servers, and Agent Skills standards.

  • Develop and maintain data pipelines for ingesting, validating, deduplicating, and updating diverse data sources into knowledge bases.

  • Build and improve the eval and observability layer to measure and ensure LLM quality, cost, and latency.

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.

Apply