Data Engineering and Development VP

State Street•Quincy, MA

1d•$120,000 - $217,500•Onsite

About The Position

State Street is seeking a dynamic, forward-thinking technology leader to shape enterprise technology capabilities by combining technical depth with strategic vision. The role leads the development and evaluation of advanced capabilities across business domains, mentors teams, influences stakeholders, and turns emerging technology into practical enterprise solutions. As Data Engineering Lead, this position leads the design, development, and deployment of solutions for document processing, intelligent agents, and automation frameworks. It works with cross-functional teams to translate business needs into data-driven workflows, establishes reusable frameworks and scalable components, and promotes secure, compliant, explainable, and robust deployments. The role prioritizes initiatives, manages delivery timelines, and aligns work with enterprise goals. The position defines data architecture patterns for fund accounting, custody, and reference data, with clear lineage from source systems through consumption layers. It partners with business and technology stakeholders to model investment data concepts and establishes scalable data models, integration standards, and quality controls supporting accounting, custody servicing, reconciliation, regulatory reporting, and client-facing data delivery. Architecture decisions must balance domain expertise, governance, performance, security, reuse, and client delivery needs. The role is based at the John Adams Building in North Quincy, Massachusetts, with stated work hours of 9:00 AM to 5:00 PM EST. The annual salary range is $120,000 to $217,500 for the specified location.

Requirements

Overall 12+ years of experience 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.
Proven ability to design, deploy, and evaluate machine learning and generative AI models.
Solid understanding of modern data engineering concepts and emerging technologies.
Experience with Python and relevant 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 practices, including fairness, transparency, and safety.
Experience building reusable components, libraries, and frameworks.
Comfort using 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 and ability to work independently and guide teams under general supervision.
Effective communication and collaboration skills, including experience influencing cross-functional teams and stakeholders in complex, regulated environments.

Nice To Haves

Java experience.
Experience with AI platforms such as OpenAI, Hugging Face, and Azure OpenAI.
Experience with orchestration tools such as LangChain.
Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, or a related field.

Responsibilities

Lead the design, development, and deployment of solutions for 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 security, compliance, explainability, and robust deployment practices.
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 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 for accounting, custody servicing, reconciliation, regulatory reporting, and client-facing data delivery.
Make architecture decisions that balance domain expertise, data governance, performance, security, and reuse across enterprise data platforms.
Guide teams and influence stakeholders in complex, regulated environments.

Benefits

401(k) retirement savings plan with company match.
Insurance coverage including basic life, medical, dental, vision, and long-term disability, as well as optional additional coverages.
Paid time off, including vacation, sick leave, short-term disability, and leave for 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.