Managing Consultant, Databricks Engineer - Dallas

Managing Consultant, Databricks Engineer
- Dallas

Department: Data Analytics

Employment Type: Full Time

Location: Dallas

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 Dallas/Fort Worth 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 Dev Ops 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.

• 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 Big Query.
• 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, Big Query, Kafka, Amazon EMR, Docker, Kubernetes, or Terraform.
• Experience implementing enterprise data quality and governance using Great Expectations,…