Head of Enterprise Data Engineering

Position Overview

The Enterprise Data Engineering team is a mission‐critical function delivering enterprise capabilities aligned to the data strategy and technology enablement for the Chief Data Office. Reporting directly to the Chief Technology Officer and indirectly to the Chief Data Officer, the Head of Enterprise Data Engineering will lead a senior engineering team to design and execute large scale data infrastructure initiatives – from legacy transformation and application modernization to cloud adoption and scalability improvements. This role is pivotal in partnering across technical domains to implement efficient, scalable, and self‑service data solutions that drive continuous improvement and innovation.

Key Responsibilities

• Provide execution leadership and direction to teams on all aspects of data engineering for business‐facing application teams.
• Engage with primary stakeholders including the Chief Data Office, Enterprise Architecture, business leaders, and Application Portfolio Owners (e.g., Product Owners, Tech Leads).
• Define execution plans and oversee workstreams for complex projects requiring large cross‑platform collaborations.
• Collaborate with Data Architecture to ensure technical integrity and consistency of solutions while influencing peer leaders and senior stakeholders on best practices.
• Adhere to design patterns and best practices with an "Enterprise First" mindset.
• Create and manage reusable frameworks and implementation patterns for data engineering across legacy and target state solutions.
• Foster an inclusive work environment where employees feel valued and supported.
• Exhibit proactive people management including hiring, coaching, feedback, employee development, and risk management.

Required Qualifications

• Bachelor’s degree or equivalent combination of education and relevant experience.
• 15+ years of total relevant work experience and 5+ years of executive management experience.

Preferred Qualifications

• Advanced degree in computer science, information systems, engineering, or equivalent experience.
• 10+ years of data engineering people management experience.
• 5+ years of experience in building and leading senior data engineers and technologists.
• Experience with Agile practices for data delivery.
• Deep technical and domain knowledge in the asset management industry.
• Strong experience building enterprise solutions using diverse tools and programming languages on both on‑prem and cloud‑native data platforms.
• Delivery experience in transactional, operational, warehousing, and reporting/analytics data solutions.
• Thought leadership in data microservices, API product architecture, and design.
• Technical leadership or architecture experience in Data Engineering, Data Management, ETL, Big Data Hadoop, and AI/ML capabilities.
• Executive level experience supporting application portfolio modernization and cloud transformation.
• Proven experience in designing and developing on‑prem and cloud‑native relational & analytics databases.
• Deep expertise in implementing Data Warehousing, Data Lake, Data Fabric, Semantic Layers, ETL, modern data pipelines, and Big Data solutions (e.g., AWS Aurora, AWS RedShift, Databricks, Snowflake, Kafka, Spark, Dremio).
• Certification or equivalent expertise in public cloud platforms (e.g., AWS, Azure, GCP) and modern data processing & engineering tools.
• Experience supporting Data Governance, Data Privacy & Subject Rights, Data Quality, Data Lineage, and Data Security practices.
• Demonstrated ability to influence across highly matrixed, complex organizations and deliver value at scale.
• Experience leading complex projects related to system design, testing, and operational stability.

Benefits & Perks

• Hybrid Work: Eligible for up to three days per week from home.
• FINRA licenses are not required and will not be supported for this role.