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Airflow Engineer Jobs in Minnesota (NOW HIRING)

Experience with tools and technologies such as Azure DevOps, Vertex AI, AWS Bedrock, SageMaker, BigQuery, Snowflake, OpenSearch, Cloud Run, Docker, Airflow, Terraform, or comparable cloud and MLOps ...

... airflow, and thermal dissipation. * Define mechanical constraints and board outlines for printed ... Initiate Engineering Change Orders (ECs) to update 3D models and technical documentation. * Advise ...

... airflow, and thermal dissipation. * Define mechanical constraints and board outlines for printed ... Initiate Engineering Change Orders (ECs) to update 3D models and technical documentation. * Advise ...

Senior Machine Learning Engineer

Minneapolis, MN · On-site

$109K - $149K/yr

... Airflow, DVC, BentoML) • Experience deploying containerized ML services using Docker and ... and DevOps practices applied to ML systems (e.g., Git, Code Review, Metrics Evaluation) • ...

... airflow, and thermal dissipation. * Define mechanical constraints and board outlines for printed ... Initiate Engineering Change Orders (ECs) to update 3D models and technical documentation. * Advise ...

Senior Software Engineer

Minneapolis, MN · On-site +1

$127K - $168K/yr

Senior Software Engineers are expected to use approved AI tools responsibly, lead by example, and ... Airflow, Composer, and Terraform Surescripts embraces flexibility through its Flexible Hybrid Work ...

Showing results 21-40

Airflow Engineer information

What is the difference between Airflow Engineer vs Data Engineer?

AspectAirflow EngineerData Engineer
CredentialsOften requires knowledge of Python, SQL, and cloud platformsRequires similar skills plus database management and ETL experience
Work EnvironmentFocuses on designing and maintaining workflows in data pipelinesBuilds and manages data infrastructure and pipelines
Industry UsageCommon in data-driven companies, analytics teams, and cloud servicesUsed across industries for data integration, storage, and processing

While both roles involve data workflows, an Airflow Engineer specializes in creating and managing workflows using Apache Airflow, whereas a Data Engineer handles broader data infrastructure and pipeline development. The roles often overlap, but the Airflow Engineer focuses more on workflow orchestration within the data ecosystem.

Infographic showing various Airflow Engineer job openings in Minnesota as of August 2026, with employment types broken down into 89% Full Time, 7% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Managing Consultant, Databricks Engineer - Minneapolis

Thought Logic Consulting

Bloomington, MN • On-site

$120 - $190/hr

Other

Posted 2 days ago

New


Job description

Managing Consultant, Databricks Engineer/Architect - Minneapolis

Department: Data Analytics

Employment Type: Full Time

Location: Minneapolis

Description

Thought Logic Consulting is a functionally-led, digitally enabled consultancy that exists at the intersection of business transformation and technology innovation. We partner with clients to solve their most complex business problems through a combination of deep functional expertise, modern technology, and practical execution. Our highly collaborative, local-market approach gives clients senior-level attention while giving our consultants room to grow, lead, and build.

***Candidates must currently reside in or live within a commutable distance to the Minneapolis Office/Twin Cities Metro ****

The Role

We are looking for a technically skilled and motivated Databricks Engineer/Architect with 7+ years of experience and strong hands-on Databricks expertise to join our growing Data & Analytics team.

In this role, you'll design and build modern data solutions for clients, with a focus on Databricks Lakehouse architecture, scalable data pipelines, cloud data platforms, data quality, and emerging AI-enabled engineering practices. You'll work alongside experienced architects and consultants while taking ownership of technical delivery and developing your client-facing and consulting skills.

What You'll Do
  • Design and build scalable data engineering solutions using Databricks Lakehouse, including Delta Lake, Unity Catalog, Delta Live Tables/Lakeflow Declarative Pipelines, Delta Sharing, and Uniform (Iceberg) where appropriate.
  • Develop and optimize batch, micro-batch, and streaming data pipelines using Auto Loader, Apache Spark, PySpark, SQL, and Python.
  • Build robust ETL/ELT processes, data models, and orchestration workflows using Databricks Jobs/Workflows, Airflow, dbt, and modern data engineering patterns.
  • Implement data quality, observability, governance, auditability, and performance optimization capabilities across enterprise data platforms.
  • Establish modern CI/CD and DevOps practices for data engineering, including Databricks Asset Bundles, automated testing, deployment automation, and Infrastructure as Code with tools such as Terraform.
Who You'll Work With
  • Experienced consultants, architects, and engineers focused on solving complex business and technology challenges through data.
  • Clients across industries looking to modernize data platforms, improve data accessibility and quality, and create greater value from their data.
  • Cross-functional stakeholders across technology, analytics, business operations, and leadership, requiring both technical depth and strong communication.
  • A collaborative team that values curiosity, humility, technical excellence, hands-on problem-solving, and client impact.
What You'll Bring
  • 7+ years of data engineering/architecture, analytics, or related technical experience, including at least 2 years of hands-on Databricks and strong experience with Lakehouse technologies.
  • Strong hands-on skills with Databricks, Delta Lake, Unity Catalog, Lakeflow/Delta Live Tables, Apache Spark, PySpark, SQL, and Python, including scalable batch and streaming pipelines.
  • Experience with Databricks Workflows/Jobs, Auto Loader, Airflow, dbt, and/or similar orchestration and transformation technologies, plus experience with cloud data platforms such as Snowflake, Redshift, or BigQuery.
  • Understanding of enterprise data quality, governance, observability, auditability, performance optimization, CI/CD, and automated testing, with exposure to Databricks Asset Bundles and Terraform.
  • Strong consulting, communication, and problem-solving skills, with the ability to work directly with technical and non-technical stakeholders and translate business requirements into practical data solutions.
Bonus Points if You Have
  • Databricks Data Engineer Associate or Professional certification and multiple Databricks project delivery experiences.
  • Experience with modern data and cloud technologies such as Snowflake, Redshift, BigQuery, Kafka, Amazon EMR, Docker, Kubernetes, or Terraform.
  • Experience implementing enterprise data quality and governance using Great Expectations, Collibra, dbt, or Databricks-native capabilities.
  • Exposure to agentic AI and AI-powered development tools, including LangGraph, autonomous agents, GitHub Copilot, Claude Code, Cursor, Windsurf, Codex, or similar technologies.
  • Previous consulting or client-facing technical delivery experience, along with cloud or additional data engineering certifications.
Why Thought Logic
  • Work on transformations that matter, not slide decks that sit on shelves
  • Real responsibility and ownership over how work gets delivered and how clients experience us
  • Direct access to firm leadership and influence over how we grow and evolve
  • A culture that values depth over optics, outcomes over activity, and people over process
  • The chance to grow your career in a firm that’s scaling thoughtfully and intentionally, not just chasing growth for growth’s sake
  • The opportunity to flex in a continuous learner environment. Get access and exposure to the latest tools, technologies and trends in the AI space
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