Data Engineering Senior Manager

Reporting to the Data Platform and Engineering Director, the Data Engineering Senior Manager leads the design, build, and optimization of the scalable data platforms that power analytics, machine learning, and AI across the firm. As a hands-on leadership role, it will set technical direction, grow a high-performing engineering team, and deliver the secure, reliable, high-performing data products that make better decisions possible firmwide.

Partnering closely with colleagues in AI, business intelligence, product, and operations, this role will turn the Firm’s data strategy into working systems while upholding rigorous data privacy and governance standards.

Duties and Responsibilities:

Translate the Firm’s data strategy into execution, delivering initiatives that hold data quality, security, and performance to a high standard and keep them aligned with business objectives.

Decompose high-level data strategy and roadmap into clearly scoped epics, user stories, and sprint-ready deliverables, driving execution and prioritization through the team’s Jira backlog.

Own the implementation and ongoing enhancement of scalable data architectures that power analytics, machine learning, and AI capabilities.

Shape the firm’s conceptual and logical data models, contributing hands-on while providing technical direction and mentorship to data architects on modeling standards and best practices.

Lead the development and continuous evolution of robust, business-aligned data platforms and pipelines, championing modern tooling such as cloud-native services, distributed computing, orchestration, and real-time streaming.

Drive the consolidation of fragmented, siloed data into a single, trusted source of truth that powers enterprise analytics and reporting.

Partner with teams across AI, BI, Product, Operations, and support to align on priorities and deliver integrated, dependable execution.

Design and implement the processes and tooling that give the firm clear data visibility and observability, turning raw data into actionable, trusted insight.

Strengthen data governance practices that safeguard data integrity, accessibility, and compliance with applicable regulations such as GDPR and CCPA.Communicate technical concepts and progress clearly to both technical and non-technical stakeholders, keeping work aligned with broader data and technology goals.

Evaluate third-party tools, services, and vendors, recommending choices that fit the firm’s technical direction and budget.undefined

Hire, develop, coach, and supervise direct reports, and conduct annual performance reviews.

Education and/or

Experience:

Required:

Bachelor's degree in Computer Science, Engineering, Data Science, or a related fieldA minimum of 10 years of experience in data engineeringA minimum of 3 years in a technical leadership or team management role Advanced knowledge of big-data architecture and distributed processing, including tools such as Spark and Kafka and Lakehouse or Data Lake patterns

Advanced proficiency in SQL and Python, with strong command of ELT/ETL tooling (e.g., dbt) and workflow orchestration (e.g., Airflow)
Strong conceptual and logical data modeling skills, with the ability to set modeling standards and guide architect-level staff

Skilled at crafting compelling data narratives through tables, reports, dashboards, and other visualization tools

Demonstrated leadership abilities in building, mentoring, and scaling high-performing, cross-functional data engineering teams in a dynamic environment

Proven experience building and scaling data platforms in a major cloud environment (AWS, Azure, or GCP) with a focus on scalability, security, and performance

Proven experience leading large-scale data migrations and consolidating disparate systems into…