Manager, Data Engineering

Advice & Wealth Management Technology (AWMT) is seeking a Data Engineering Manager to lead a team delivering scalable data platforms and products that power personalized financial advice.

You will own delivery, engineering standards, and talent development while partnering across product, analytics, and ML teams to enable production-grade data and GenAI capabilities.

Responsibilities:

• Lead a team of data engineers to build and operate scalable, reliable data pipelines and platforms
• Drive engineering excellence (code quality, CI/CD, testing, observability, incident management)
• Partner with product and analytics to prioritize and deliver high-impact data use cases
• Own production support, incident response, and continuous improvement of data systems
• Establish and scale DataOps practices across development and operations
• Collaborate across AWMT D&A to enable data products that support personalization and analytics
• Hire, develop, and grow engineering talent and future tech leads
• End-to-end delivery and operation of data pipelines and platforms supporting advice products
• Engineering quality, reliability, and standardization across your team
• Talent development for data engineers and tech leads
• Cross-team alignment with product, analytics, and ML engineering
• Improving reliability and observability of production data pipelines
• Driving adoption of consistent pipeline frameworks and engineering standards
• Enabling scalable data foundations for ML and GenAI use cases
• Strengthening team execution, prioritization, and stakeholder trust

• Experience leading data engineering teams delivering production data platforms
• Strong understanding of modern data architectures and cloud-based data ecosystems
• Track record of improving engineering quality, reliability, and delivery at scale
• Experience partnering with product, analytics, and ML teams
• Demonstrated ability to develop engineers and build high-performing teams
• Cloud-native data platforms (AWS: S3, Glue, Athena, etc.)
• Batch and event-driven data pipelines
• Data modeling and large-scale data processing
• Data platforms supporting ML and GenAI use cases
• Observability, monitoring, and operational excellence for data systems
• Minimum of eight years data analytics, programming, database administration, or data management experience.
• Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.

• Exposure to ML or GenAI data workflows
• Financial services or regulated environment experience