Vice President, Data Architecture

Fidelity•Durham, NC

About The Position

Fidelity is seeking an experienced architect to lead a team of data architects within Asset Management Technology. The role sets technology strategy and execution direction across Research, Portfolio Management, and Trading, supporting a business with $7 trillion in assets. The Vice President will guide the data architecture practice, create AI-ready platforms and governance frameworks, and develop a high-performing architecture team. The position defines data architecture strategy aligned with business objectives; establishes platform standards, design patterns, and guardrails; and positions data platforms for AI through appropriate semantic and data-access layers. It partners with product management, engineering leadership, and business stakeholders to turn complex requirements into architectural roadmaps and delivery plans. The role combines team leadership with hands-on architectural work, including design, prototyping, and code contributions for critical data challenges. It encompasses enterprise-scale data platforms and pipelines for transactional, operational, and analytical workloads, reference architectures and accelerators, and technical reviews that ensure solutions meet requirements for scalability, security, compliance, maintainability, performance, observability, and operational resilience. The Asset Management Technology group supports Fidelity’s investment management business. Its Architecture team provides technical vision and leadership for key initiatives and complex solutions across Research, Portfolio Management, and Trading. Fidelity is transitioning to a full-time onsite model through a phased regional and role-based rollout; current onsite expectations vary, may evolve, and do not apply to fully remote roles. Fidelity will not provide immigration sponsorship for this position. The business is subject to financial-services laws and regulations that may restrict hiring or association with individuals with certain criminal histories.

Requirements

Bachelor's degree in Computer Science, Information Technology, or a related technical field.
Five years leading, mentoring, and developing technical teams.
Experience building teams or transforming underperforming teams into high-performing organizations, demonstrated through hiring, retention, and team members’ career progression.
Proven ability to mentor and develop architects and senior engineers, including helping individuals progress from mid-level to staff or principal roles.
Executive-level communication skills, including presenting to senior audiences, translating technical concepts into business language, articulating risk-reward trade-offs, and building consensus among stakeholders.
Expert-level proficiency in SQL, PL/SQL, and modern data programming languages, including Python, Scala, and Java; ability to review code, conduct technical interviews, and contribute to critical implementations.
Deep experience with modern data engineering toolchains, including Spark, Kafka, Airflow, dbt, Snowflake, Databricks, and cloud-native services such as AWS Glue, Lambda, Step Functions, and Kinesis.
Understanding of the operational characteristics, failure modes, and cost implications of data engineering technologies at enterprise scale.
Expertise in DataOps and continuous delivery for data platforms, including infrastructure as code with Terraform or CloudFormation, CI/CD for data workflows, automated testing for data quality, schema validation and lineage, and observability instrumentation.

Nice To Haves

Master's degree or MBA.
Advanced degree or certification in Data Science, Machine Learning, or Systems Engineering.

Responsibilities

Define and evangelize data architecture strategy across Asset Management Technology, aligning technical direction with business objectives and competitive advantage.
Lead architecture governance and establish data-platform design patterns, standards, best practices, and guardrails.
Position data platforms to be AI-ready through appropriate semantic and data-access layers.
Partner with product management, engineering leaders, and business stakeholders to translate requirements into architectural roadmaps and delivery plans.
Hire, onboard, develop, and plan succession for data architects; establish career-growth paths and foster technical excellence and continuous learning.
Lead hands-on design, prototyping, and code contributions for complex and critical data challenges.
Design and optimize enterprise-scale data platforms, ETL/ELT pipelines, data-access layers, and polyglot persistence strategies for transactional, operational, and analytical workloads.
Establish reference architectures and accelerators that promote consistent security, observability, performance, and operational resilience while reducing time to market.
Lead technical deep dives and design reviews, unblock teams, validate approaches, and ensure solutions meet non-functional requirements, including scalability, security, compliance, and maintainability.
Mentor architects and senior engineers through coaching, design-review feedback, exposure to complex problems, and career advocacy.