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 preferred.
- 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
Pay: $170,000.00 - $180,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Flexible spending account
- Health insurance
- Health savings account
- Life insurance
- Paid time off
- Parental leave
- Vision insurance
Application Question(s):
- Are you located in the Chicagoland area, residing in the state of IL?
- Will you now, or in the future, require employer sponsorship to work in the United States?
- This position requires three days per week onsite at our Chicago, IL office. Do you confirm that you are able to meet this requirement?
- Do you have experience with SQL?
- Do you have experience with Apache Airflow on MWAA
- Do you have experience with AWS Glue Data Catalog / DataZone?
- Do you have exrience with QuickSight, Periscope?
- Do you have experience with SageMaker?
- Do you have experience with Python?
- Are you willing to undergo a background check, in accordance with local law and regulations?
Education:
Experience:
- Team Leadership and development: 2 years (Required)
Ability to Commute:
- Chicago, IL 60603 (Required)
Work Location: Hybrid remote in Chicago, IL 60603