Data Engineering Manager in Chicago

Job DescriptionJob Description

About the Role

We are a financial services company hiring a Data Engineering Manager to lead a small, high-impact team building the data infrastructure behind our loan performance, portfolio analytics, and operational reporting. This is a hands-on leadership role. You will write code, set engineering standards, and drive delivery while also managing people and partnering with data scientists, analysts, and software engineers across the organization.

If you want a role where you can architect real systems, grow a team, and have a direct line to business outcomes, this is it.

What You’ll Do

Team Leadership

• Lead and mentor a team of data engineers and BI analysts, including performance feedback and career development.

• Own sprint planning, estimation, prioritization, and delivery tracking.

• Coordinate intake and stakeholder communication for data requests and roadmap planning.

• Set and enforce engineering standards for code quality, testing, documentation, and production readiness.

• Partner with leadership on hiring, team structure, and quarterly planning.

Data Pipelines and Integration

• Design, build, and maintain ETL/ELT pipelines from transactional systems, internal services, and third-party APIs.

• Build automated, scalable data workflows using Apache Airflow (MWAA) or similar orchestration tools.

• Implement incremental processing, change data capture, and data quality checks.

• Support analytics use cases including loan performance metrics, portfolio analysis, and risk modeling.

Data Warehouse and Modeling

• Build and manage data warehouse environments, primarily AWS Redshift and RDS PostgreSQL.

• Design dimensional and normalized data models for BI reporting and analytics.

• Optimize schema design, query performance, and materializations for analytical workloads.

• Lead data validation, profiling, reconciliation, and quality initiatives.

Reliability and DevOps

• Implement CI/CD and infrastructure-as-code practices for data workflows and environments.

• Build monitoring and alerting for data jobs, orchestration, and warehouse health.

• Participate in production support, incident response, and on-call rotations as needed.

What We’re Looking For

• 3-5 years leading or managing data engineering and/or BI teams.

• 5-8 years of hands-on data engineering experience in analytics-driven environments.

• Strong SQL and Python skills for data transformation, modeling, and troubleshooting.

• Practical experience with modern orchestration and transformation tools (Airflow, SQLMesh, or similar).

• Solid understanding of data warehouse modeling patterns (dimensional and normalized).

• Experience with data quality validation, monitoring, and production support.

• Familiarity with cloud data platforms, AWS strongly .

• Comfortable driving sprint-based execution and aligning cross-functional stakeholders.

Our Tech Stack

You will work directly with many of these tools:

• AWS Redshift, RDS PostgreSQL

• Apache Airflow on MWAA

• SQLMesh

• AWS Glue Data Catalog / DataZone

• QuickSight, Periscope

• SageMaker

• Python

Compensation and Benefits

Salary: $170,000 – $180,000

Bonus: 10% annual target bonus based on company and individual performance.

Benefits include:

● Medical, Dental, and Vision coverage

● Basic and Voluntary Life Insurance

● 401(k) with company match

● Short-Term and Long-Term (STD / LTD)

● Employee Assistance Program (EAP)

● Commuter Plan

● FSA / HSA

● MetLife Ancillary Benefits

● Paid Time Off (PTO)

● Paid Sick Leave

● Floating Holidays

● Paid Parental Leave