Managing Consultant, Databricks Engineer/Architect - Birmingham, AL

Managing Consultant, Databricks Engineer/Architect - 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 Birmingham, AL Clients **** 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.

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.