Senior Manager Data Engineer

This role is for a Senior Manager Data Engineer working onsite in Chicago, IL with the Information Technology Senior Management Forum. You will lead and mentor data engineering leaders and teams while guiding the design, development, and ongoing support of scalable cloud-first data engineering solutions.

The position emphasizes both technical depth and people leadership, with a hands-on approach to reviewing architecture, data models, and pipeline code across modern data platforms. The work spans lakehouse-oriented engineering with tools such as Databricks, PySpark, and Snowflake, alongside broader cloud and orchestration ecosystems.

Responsibilities

• Lead high-performing Agile teams to design, develop, test, and support scalable data engineering solutions across full-stack and cloud platforms.
• Influence and elevate a team of developers, data analysts, and data scientists with experience across machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Stay hands-on through review of architecture designs, data models, and pipeline code using Python, Spark, Databricks, and Snowflake.
• Drive continuous learning by experimenting with new technologies, participating in internal and external technology communities, and mentoring others in the data community.
• Collaborate with product managers and software engineers to deliver robust cloud-first data solutions that support powerful experiences for financial empowerment.
• Architect and enforce common data engineering design patterns to support code quality, maintainability, and reusability.
• Serve as an ambassador for the data engineering team by communicating technical concepts and data outcomes clearly to internal and external stakeholders to support alignment.
• Oversee the design and health of data platforms and pipelines, setting standards for scalability, resilience, data quality, and operational efficiency.
• Lead, mentor, and grow a diverse team of data engineers while improving talent density, fostering technical career development, and promoting engineering best practices.
• Lead and execute large-scale, transformative data initiatives end to end, including critical architectural decisions and platform evaluations such as Snowflake versus Databricks.

Requirements

• Bachelor’s Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
• 6+ years of experience in application development (internship experience does not apply).
• 3+ years of people management experience.
• 2+ years driving technical delivery of roadmap features.
• 4+ years programming with at least one of: Python, Java, or Scala.
• 4+ years designing and developing data pipelines.
• 2+ years in data modeling and designing end-to-end data solutions using both relational and non-relational database systems.

Technologies

• Databricks, PySpark, Snowflake, Python, Java, Scala, Spark
• Machine learning, distributed microservices, lakehouse architecture
• AWS, Microsoft Azure, Google Cloud, EMR, Glue
• Airflow, Dagster
• Monte Carlo, Splunk
• MongoDB, Cassandra, DynamoDB, Redshift, NoSQL, SQL

Benefits

• Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.

Preferred Qualifications

• Master’s Degree in Computer Science or a related field.
• 9+ years of application development with demonstrated proficiency in Python, SQL, Scala, or Java.
• 5+ years hands-on experience designing, deploying, and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud).
• 5+ years experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks.
• 5+ years experience designing, implementing, and operating real-time or streaming data pipelines.
• 3+ years experience in data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster).
• 5+ years experience working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB).
• 5+ years experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift).
• 3+ years experience working in an Agile development environment.
• 3+ years experience developing user-centric reusable data products.

Salary

Chicago, IL: $209,000 - $238,500 per year for Sr. Manager, Data Engineer.