Data Engineering Manager
$121,000–$215,000 year
HybridChicago, Illinois, United States or Houston, Texas, United States
Job Summary
Lead the design and build-out of the firm's cloud-based data platform from the ground up, establishing foundational infrastructure for analytics, reporting, applications, and AI. Architect core systems to collect, consolidate, and organize data efficiently while setting standards for data engineering methods and product reliability. Supervise all Data Engineering staff, fostering professional growth through regular performance evaluations, constructive feedback, and clear goal setting. Partner with Data Science, IT Operations, and business leaders to translate challenges into platform improvements and manage vendor relationships. Define and enforce best practices for code quality, testing, deployment, and documentation across the firm. Manage project planning, timelines, and risks while ensuring scalable, maintainable, and secure data solutions.
Required Qualifications
- Bachelor's degree in computer science, engineering, information systems, or related field, or equivalent industry experience
- At least 3–5 years of experience leading data engineering or closely related technical teams
- Experience managing budgets and making cost conscious decisions about tools, platforms, and services
- Strong understanding of modern data engineering practices, including data ingestion, consolidation, transformation, and organization to support analytics and AI
- Extensive experience with data management and data transformation, including performance, reliability, and scalability considerations
- Advanced SQL experience and strong understanding of how to design and optimize data structures in relational and other data storage technologies
- Experience designing and managing data solutions in modern cloud environments (for example, Microsoft Azure or Amazon Web Services), including use of platform services
- Working knowledge of Python and common data tooling, with sufficient depth to review designs and solutions produced by engineers and to engage effectively with Data Science & AI teams
- Demonstrated experience collaborating with data scientists, analysts, and AI practitioners, and understanding how engineering choices affect downstream analytics and AI work
- Broad familiarity with data visualization, reporting, and application needs so that data platforms are designed with end to end use in mind
- Extensive experience with software development life cycle and software engineering best practices, including version control, testing, deployment, monitoring, and secure handling of data
- Ability to define and implement data and platform standards, and to guide teams in adopting consistent, high quality engineering practices
- Graduate degree preferred
Desired Qualifications
- graduate degree preferred
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