Data Engineering and Development VP

State Street•Quincy, MA

1d•$120,000 - $217,500•Onsite

About The Position

The Data Engineering and Development VP is a hands-on technology leader responsible for shaping and delivering data engineering and advanced technology capabilities across enterprise business domains. The role guides the design, development, deployment, and evaluation of solutions such as document processing, intelligent agents, and automation frameworks, while translating business requirements into data-driven workflows. It establishes reusable frameworks, evaluation pipelines, scalable components, and responsible practices for secure, compliant, explainable, and robust solutions. The position defines and evolves data architecture patterns for fund accounting, custody, and reference data. It partners with business and technology stakeholders to model investment data concepts and establish scalable data models, integration standards, lineage, quality controls, reconciliation, and governance. Architecture decisions must balance domain expertise, performance, security, reuse, regulatory needs, and client data delivery. The role also prioritizes initiatives, manages delivery timelines, mentors teams, and influences stakeholders in complex, regulated environments. The role is based at the John Adams Building in North Quincy, Massachusetts, with stated work hours of 9:00 a.m. to 5:00 p.m. EST. The salary range is $120,000 to $217,500 annually, with the applicable range potentially varying by work location.

Requirements

Overall 12+ years in IT delivery, including 3+ years of hands-on experience in AI/ML and data engineering.
Strong foundation in enterprise-scale solution development.
Strong hands-on expertise in Python, Apache Spark, PySpark, and Databricks for large-scale data processing and AI model development.
Experience with Python libraries such as FastAPI, PyTorch, TensorFlow, and Pandas.
Familiarity with distributed systems, orchestration tools, and API integration.
Strong foundation in software engineering principles, including OOPS, design patterns, data structures, and algorithms.
Ability to manage and support multiple workflows or agents in parallel.
Awareness of responsible technology principles and practices, including fairness, transparency, and safety.
Experience building reusable components, libraries, and frameworks to accelerate development.
Comfort using tools such as Fiddler and Postman for API development and debugging.
Deep understanding of fund accounting, custody, and reference data domains, and ability to connect business concepts to scalable data architecture.
Strong data modeling skills across positions, transactions, cash, income, securities, accounts, and party/reference data.
Experience designing data lineage, data quality, reconciliation, and governance controls for regulated financial services platforms.
Ability to balance domain knowledge, engineering discipline, platform reuse, and client delivery needs in architecture decisions.
Proactive mindset, ability to work independently, and ability to guide teams under general supervision.
Effective communication and collaboration skills, with experience influencing cross-functional teams and stakeholders in complex, regulated environments.

Nice To Haves

Java experience.
Experience designing, deploying, and evaluating machine learning and generative AI models using platforms such as OpenAI, Hugging Face, and Azure OpenAI.
Experience with orchestration tools such as LangChain.
Solid understanding of AI evaluation frameworks and responsible AI practices.

Responsibilities

Lead the design, development, and deployment of solutions for use cases such as document processing, intelligent agents, and automation frameworks.
Collaborate with cross-functional teams to translate business needs into data-driven workflows using modern orchestration tools.
Promote responsible practices, including security, compliance, and explainability, and ensure robust deployment.
Establish reusable frameworks, evaluation pipelines, and scalable components to accelerate adoption and maintain consistency.
Prioritize initiatives, manage delivery timelines, and align efforts with enterprise goals.
Define and evolve data architecture patterns for fund accounting, custody, and reference data domains, ensuring clear lineage from source systems through consumption layers.
Partner with business and technology stakeholders to model investment data concepts, including NAV, positions, transactions, cash, income, corporate actions, securities, accounts, and party/reference data.
Establish scalable data models, integration standards, and quality controls supporting accounting, custody servicing, reconciliation, regulatory reporting, and client-facing data delivery.
Drive architecture decisions that balance domain expertise, data governance, performance, security, and reuse across enterprise data platforms.
Guide teams and influence stakeholders while supporting multiple workflows or agents in parallel.

Benefits

Retirement savings plan (401K) with company match.
Insurance coverage including basic life, medical, dental, vision, long-term disability, and optional additional coverages.
Paid time off including vacation, sick leave, short-term disability, and family care responsibilities.
Access to an Employee Assistance Program.
Incentive compensation, including eligibility for annual performance-based awards, subject to stated exclusions.
Eligibility for certain tax-advantaged savings plans.
Inclusive development opportunities.
Flexible work-life support.
Paid volunteer days.
Employee networks.