Job Description
Managing Consultant, Databricks Engineer - Minneapolis
Department: Data Analytics
Employment Type: Full Time
Location: Minneapolis
Managing Consultant, Databricks Engineer - Minneapolis
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 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
What You'll Bring
- 7+ years of data engineering, analytics, or related technical experience, including at least 2 years of hands-on Databricks engineering 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
