Data Engineering Manager

Data Engineering Manager | Enterprise Data + AI Transformation | Chicago

I'm partnering with a globally renowned law firm undertaking one of the most consequential Data & AI transformations in its sector.

We're searching for an exceptional Data Engineering Manager to lead the team responsible for turning a newly established enterprise data platform into a production engine for analytics, reporting, data products and emerging AI capabilities.

The architecture is established. The executive investment is there. The broader Data & AI organization is approaching 100 professionals
.

Now comes the difficult part:
execution.

We're looking for the leader who can take sophisticated architecture and turn it into exceptional engineering delivery.

You'll lead approximately 7–9 Data Engineers and consultants
, partnering closely with Data Architecture and BI while owning technical execution, engineering quality, team development and delivery.

This is deliberately not a role for a career manager who has spent years away from the technology.

Nor is it an architect position where success means producing diagrams and strategy decks.

We want someone who can sit between both worlds.

• Engineering execution across a modern enterprise data platform
• Development and transformation of complex enterprise datasets
• ETL/ELT and scalable batch/streaming pipelines
• Code reviews and engineering standards
• Data quality, testing, monitoring and SLAs
• Technical design and troubleshooting
• Team performance, mentorship and career development
• Consultant management and accountability
• Partnership across Data Architecture, BI and business stakeholders
• Production readiness and adoption of a rapidly evolving data ecosystem

You likely spent 6+ years as a genuinely hands-on Data Engineer before moving into leadership and have 2–4+ years of meaningful team leadership or management
.

You haven't forgotten how the technology works.

You can still review Python and SQL
, understand pipeline architecture, challenge a design decision, diagnose why a transformation is failing and earn credibility with excellent engineers.

Experience with
Databricks, Snowflake or another sophisticated modern cloud data platform is highly relevant.

We're particularly interested in experience spanning:

Python | SQL | Spark/PySpark | ETL/ELT | Lakehouse Architecture | Data Modeling | CI/CD | Testing | Data Quality | Cloud Data Platforms | Batch/Streaming | Governance

Azure experience is advantageous, but excellent AWS and GCP engineers are absolutely encouraged to apply
.

We're looking for someone who is confident, decisive and comfortable creating accountability
.

You should be able to manage high-performing engineers, challenge consultants, resolve conflict, address performance issues and keep complicated engineering initiatives moving without becoming a micromanager.

Because very few opportunities combine the resources, prestige and stability of a globally renowned institution with the opportunity to join a Data & AI organization while its next generation is still being built.

You won't spend your first year fighting for investment or writing a platform strategy that may never be funded.

The foundation exists.

Your opportunity is to make it exceptional.

Chicago hybrid, 3 days onsite. Competitive base + bonus + comprehensive benefits.