Vice President, Data Architecture

Fidelity•Merrimack, NH

1d•Onsite

About The Position

Fidelity is actively seeking an experienced architect to lead a team of data architects in the Asset Management Technology’s architecture team. At Fidelity, architects are leaders in technology playing a significant role in driving all aspects of technology planning and execution. Fidelity's Asset Management Technology group is seeking a visionary leader to helm our data architecture practice, guiding technical strategy across Research, Portfolio Management, and Trading functions supporting $7 trillion in assets. You will set the architectural direction for AI-ready platforms, establish governance frameworks that enable consistent excellence, and build a high-performing team of architects positioned to tackle the most consequential data challenges in financial services.

Requirements

Bachelor's degree in Computer Science, Information Technology, or a related technical field required; master's degree or MBA preferred.
5 years leading, mentoring, and developing technical teams, with experience building teams from the ground up or transforming underperforming teams into high-performing organizations, demonstrated through successful hiring, strong retention, and career progression of team members to senior or principal roles.
Proven ability to mentor and develop architects and senior engineers, with a track record of growing individuals from mid-level to staff or principal levels through coaching, design review feedback, exposure to complex problems, and advocacy for career advancement.
Executive-level communication skills, with the ability to present to senior audiences, translate complex technical concepts into business language, articulate risk and reward trade-offs, and build consensus among stakeholders with competing priorities.
Expert-level proficiency in SQL, PL/SQL, and modern data programming languages, including Python, Scala, and Java, with the ability to review code, conduct technical interviews, and contribute to critical implementations when needed while maintaining technical credibility through periodic hands-on work on complex problems.
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, with an understanding of their operational characteristics, failure modes, and cost implications at enterprise scale.
Expertise in DataOps and continuous delivery practices for data platforms, including infrastructure as code using Terraform or CloudFormation, CI/CD pipelines for data workflows, automated testing strategies for data quality, schema validation, and lineage, and observability instrumentation.

Nice To Haves

Advanced degrees or certifications in Data Science, Machine Learning, or Systems Engineering add differentiation.

Responsibilities

Define and evangelize data architecture strategy across Asset Management Technology, establishing technical direction that aligns with business objectives and drives competitive advantage while balancing innovation with operational excellence.
Lead architecture governance and standards for data platforms, establishing design patterns, best practices, and guardrails that enable teams to deliver consistent, scalable solutions while maintaining architectural coherence across the organization.
Position data platforms to be AI-ready with appropriate semantic and data access layers.
Drive cross-functional data initiatives as a senior technical leader, partnering with product management, engineering leadership, and business stakeholders to translate complex business requirements into actionable architectural roadmaps and delivery plans.
Build and develop high-performing data architecture teams through hiring, onboarding, career development, and succession planning—creating clear growth paths from mid-level to senior architect roles and fostering a culture of technical excellence and continuous learning.
Architect and deliver high-impact solutions for the most complex and critical data challenges, leading by example through hands-on design, prototyping, and code contributions that set quality standards and demonstrate technical excellence to the team.
Design and optimize enterprise-scale data platforms encompassing ETL/ELT pipelines, data access layers, and polyglot persistence strategies for transactional, operational, and analytical workloads using modern cloud-native patterns and Fidelity-preferred technology stacks.
Establish reference architectures and accelerators that encode proven patterns for common use cases, reducing time to market for teams while ensuring consistency in security, observability, performance, and operational resilience.
Lead technical deep dives and design reviews for critical initiatives, providing architecture expertise that unblocks teams, validates approaches, and ensures solutions meet non-functional requirements, including scalability, security, compliance, and maintainability.