POSITION OVERVIEWThe Data Engineering Manager is a senior technical and people leadership role within Global Data Services (GDS). This position is responsible for leading data engineering teams, owning critical data platforms and processing components, driving operational excellence, and establishing best practices for data architecture, software engineering, and data management.
This role combines strategic leadership, technical expertise, operational accountability, and innovation to ensure Urban Science delivers reliable, scalable, secure, and high-quality data solutions that support products, client systems, analytics, and business operations.
This role has current Hybrid Workplace flexibility local to our Detroit, MI office location. Candidates must be available and willing to work in-person two days per week.Essential Duties and ResponsibilitiesESSENTIAL DUTIES AND RESPONSIBILITIES- Leadership & Team Management
- Lead, mentor, and develop Data Engineering team members.
- Manage performance, career development, succession planning, and staffing needs.
- Foster collaboration across Technology, Product, Analytics, Practice, and Client-facing teams.
- Provide technical leadership and establish engineering best practices across the organization.
- Communicate team performance, priorities, risks, and KPIs to leadership.
- Data Engineering & Architecture
- Design, build, and maintain scalable data pipelines, platforms, and processing systems.
- Own and evolve one or more critical data processing capabilities within GDS.
- Define data architecture standards and ensure solutions support business, product, and analytics requirements.
- Integrate data from diverse internal, client, and third-party sources.
- Apply software engineering, distributed systems, and data management best practices to all solutions.
- Operations & Delivery
- Ensure reliable, efficient, and sustainable day-to-day data operations.
- Oversee production processing, incident management, support processes, and service quality.
- Standardize tooling, processes, and documentation to improve scalability and reduce operational risk.
- Manage data migrations, troubleshooting, profiling, anomaly detection, and data quality initiatives.
- Ensure teams are properly resourced to support current operations and future growth.
- Innovation & Continuous Improvement
- Identify opportunities to improve data quality, reliability, performance, and cost efficiency.
- Lead proof-of-concept initiatives and evaluate emerging technologies, tools, and methodologies.
- Drive automation and modernization efforts across data platforms and processes.
- Contribute to technology strategy, architectural decisions, and enterprise-wide engineering practices.
- Governance & Compliance
- Ensure compliance with security, privacy, contractual, and regulatory requirements.
- Define and support data governance, access control, and operational policies.
- Promote sustainable, documented, and auditable data management practices.
- Champion data confidentiality and risk management across all data operations.
Qualifications - Education and ExperienceQUALIFICATIONS- Leadership & Communication
- Proven experience leading technical projects and mentoring engineers.
- Ability to communicate effectively with technical teams, business stakeholders, and senior leadership.
- Strong collaboration and relationship-building skills across global organizations.
- Technical Expertise
- Strong experience with SQL and relational database technologies, particularly Microsoft SQL Server.
- Deep understanding of data modeling, ETL/ELT, data integration, and modern data architectures.
- Knowledge of structured, semi-structured, and unstructured data platforms.
- Experience with distributed systems, APIs, microservices, and enterprise integration patterns.
- Hands-on experience with programming/scripting languages such as Python or C#.
- Strong understanding of software engineering best practices, CI/CD, testing, source control, and operational support.
EDUCATION AND/OR EXPERIENCE- Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent experience.
- 8-10+ years of experience in data engineering, software engineering, or related technical roles.
- Experience leading, projects, or major technical initiatives.
- Experience supporting large-scale data processing and analytics environments.
- 2+ years in data-related background
- Data Analytics experience is a plus
WORK ENVIRONMENTThe work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
DISCLAIMER
This description is intended to describe the type and level of work being performed by a person assigned to this position. It is NOT an exhaustive list of all duties and responsibilities required by a person so classified. The job may require additional hours beyond the normal 40-hour workweek. 
