Managing Consultant, Data Engineer
Thought Logic Consulting
Job Description
Job Description
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 and we do it in a highly collaborative, local-market approach, giving clients senior-level attention and giving our consultants room to grow, lead, and build.
The Role
We are looking for a technically skilled and motivated Data Engineer with 7-12 years of experience to join our growing Data & Analytics team. In this role, you'll work closely with cross-functional teams to build modern data pipelines, develop scalable solutions, and help clients unlock insights from their data. You’ll be supported by experienced architects and consultants while having the opportunity to grow your technical and consulting skills in a collaborative, client-facing environment.
What You'll Do
- Build and maintain scalable, reliable data pipelines using tools like Azure Data Factory, AWS Glue, or Palantir Foundry
- Develop ETL/ELT processes to transform and prepare raw data for reporting, analytics, and downstream applications
- Collaborate with team members and clients to gather requirements, integrate data sources, and ensure high data quality
- Assist in the development and optimization of data models and cloud-based data platforms (e.g., Snowflake, Databricks, Redshift)
- Support the creation of dashboards and data visualizations using tools like Power BI or Tableau
- Participate in testing, documentation, and deployment of data solutions to ensure performance and reliability
- Engage in project workstreams alongside more senior team members, gaining exposure to client interaction and delivery best practices
- Learn and apply modern data engineering and cloud practices in a variety of industries and use cases
- A team of collaborative, experienced consultants focused on solving complex business problems through data
- Clients across industries who are looking to modernize their data platforms and make more informed decisions
- Colleagues who prioritize curiosity, humility, and hands-on problem-solving
A supportive environment where ongoing learning and mentorship are central to your professional growth
- 7-12 years of professional experience in data engineering, analytics, or a related technical role
- Proficiency in SQL and working knowledge of Python or another scripting language
- Hands-on experience with ETL/ELT processes and modern data tools such as Azure Data Factory, AWS Glue, Snowflake, or Databricks
- Familiarity with cloud environments (AWS, Azure, Palantir Foundry or similar) and data modeling concepts
- Understanding of data integration, quality, and performance tuning principles
- Ability to work collaboratively on fast-paced projects with a mix of technical and non-technical stakeholders
- Strong problem-solving and communication skills
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field
- Currently reside in Minneapolis,MN area or willingness to relocate at your expense.
- Ability to legally work for any employer in the US without sponsorship
Bonus Points if You Have
- Experience with tools like Apache Airflow, dbt, or Palantir Foundry
- Familiarity with big data technologies such as Spark, Kafka, or Redshift
- Exposure to dashboarding and visualization tools like Power BI or Tableau
- Certifications in cloud platforms or data engineering technologies
- Previous consulting firm experience
- 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
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