Job DescriptionThe Manager, Data Engineering leads the design, delivery, and reliability of TAG's enterprise data platform across our multi-brand environment. It's a hands-on leadership role covering people management, architecture, platform engineering, and operations.
The right person can lead a team of Data Engineers and still do the work themselves - technical design, code reviews, incident management, platform modernization, and engineering standards. They'll also drive AI-assisted development, automation, and cloud cost optimization to keep the team productive and the platform scalable.
Key ResponsibilitiesLeadership & Delivery
- Lead, mentor, and grow a team of Data Engineers across multiple domains.
- Run sprint planning, backlog prioritization, and delivery.
- Balance strategic work, operational support, and technical debt.
- Partner with business, analytics, and technology leaders to align priorities.
Data Platform & Engineering
- Own the architecture and delivery of scalable data pipelines, semantic models, and data products.
- Set standards for data modeling, integration, and platform architecture across dbt, Airflow/Cloud Composer, BigQuery, Terraform, and CI/CD.
- Lead design reviews, evaluate new technologies, and drive platform modernization.
AI & Engineering Excellence
- Lead AI-assisted development (Claude AI/Gemini Enterprise) across code reviews, documentation, testing, and automation.
- Set standards and governance for responsible use of AI-generated code.
Reliability, Operations & Cloud
- Own data platform reliability, monitoring, incident response, and root cause analysis.
- Establish SLAs, operational metrics, and on-call processes.
- Ensure compliance with data governance, security, privacy, and access management.
- Optimize performance, scalability, and cost across GCP, including BigQuery consumption, storage, and slot utilization.
QualificationsRequired Experience
- Bachelor's degree in computer science, Engineering, Information Systems, or related field. GCP Professional Data Engineer Certification a plus.
- 7+ years of Data Engineering experience with modern cloud data platforms.
- 3+ years of leadership experience managing Data Engineering teams.
Technical Skills
- Strong expertise in SQL, Python, dbt, and Airflow/Cloud Composer.
- Hands-on experience with Google Cloud Platform, including BigQuery, GCS, Pub/Sub, Dataflow, Cloud Functions, and Vertex AI.
- Experience with Infrastructure as Code (Terraform) and CI/CD automation.
- Strong understanding of data warehousing, semantic modeling, data quality, and governance across batch, streaming, and event-driven architectures.
Leadership Competencies
- Strong communication and stakeholder management skills.
- Ability to translate business requirements into scalable technical solutions.
- Experience leading cross-functional initiatives and influencing technical direction.
- Track record of building strong teams and a solid engineering culture.
*This role is onsite 4 days/week in our Chicago office (Fulton Market District)
Annual Salary Range: $160,000-$190,000/year, with a generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match.
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