Managing Consultant, Databricks Engineer - Richmond

Thought Logic Consulting

Richmond (VA)

On-site

USD 140,000 - 200,000

Full time

2 days ago
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Job summary

Thought Logic Consulting is seeking a technically skilled Databricks Engineer to join the Data & Analytics team in Richmond. This full-time role requires 7+ years of experience and hands-on Databricks expertise to design scalable data solutions for enterprise clients.

You will work with senior consultants and engineers to build data pipelines, enforce governance, and implement CI/CD practices, delivering tangible client value and hands-on problem-solving in a collaborative, fast-paced

Qualifications

  • 7+ years of data engineering, analytics, or related technical experience.
  • Hands-on Databricks engineering experience with Lakehouse technologies.
  • Strong consulting, communication, and problem-solving skills.

Responsibilities

  • Design and build scalable data engineering solutions using Databricks Lakehouse, including Delta Lake and Unity Catalog.
  • Develop and optimize batch, micro-batch, and streaming data pipelines using Spark, PySpark, SQL, and Python.
  • Build ETL/ELT processes, data models, and orchestration workflows with Databricks Workflows, Airflow, and dbt.
  • Implement data quality, governance, observability, and performance optimization across data platforms.

Skills

Databricks engineering
Data engineering
Communication
Problem-solving

Tools

Databricks
Delta Lake
Airflow
dbt
Terraform
Apache Spark
PySpark

Job description

Managing Consultant, Databricks Engineer - Richmond

Department: Data Analytics

Employment Type: Full Time

Location: Richmond

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 Richmond area ****

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.

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, 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
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