Vice President, Data Architect, Data Service and Governance

The VP, Data Architect role is a hands-on technical leader within the Enterprise Data Service and Governance Team. This individual will design, build, and support modern data architectures that span on-premises and Azure cloud environments. This role requires deep expertise in investment management data domains. Strong hands-on data architecture skills, and the ability to translate complex investment and operational requirements into robust data models and integration patterns.

The right candidate brings deep expertise across the full data stack - from logical to physical modeling, data warehouse to data lake, analytics to reporting - and knows how to match the right platform to support the firm's investment management and operation functions. This is a thinker and a doer role: design, plan, implement, and support.

Key Responsibilities

Architecture & Design

• Architect end-to-end data solutions across on-prem and Azure cloud platforms, applying sound judgment on platform fit based on business requirements, cost, and complexity
• Lead data modeling initiatives, including logical, physical, dimensional design, across various platforms of data marts, data warehouses, and data lake
• Design and implement multi-layer ELT/ETL pipelines using Azure-native services
• Evaluate architectural tradeoffs balancing delivery velocity, data integrity, operational risk, and long-term maintainability
• Translate complex business and investment requirements into robust, scalable data models and integration patterns
• Evaluate new data product and platform

Hands-On Delivery

• Perform hands-on development alongside architecture and design work
• Conduct code and design reviews, and suggest and validate unit test cases
• Contribute to the evolving data platform by evaluating, prototyping, and adopting new technologies, * Collaborate with the Head of Data Services and Governance and Business/Data Analysts to define project design and influence requirements
• Provide technical direction, lead design discussions and resolve conflicts
• Contribute to the short- and long-term data technology roadmap
• Write and maintain domain documentation

Production Support & Issue Resolution

• Participating in on-call rotation for operational support
• Triage and troubleshoot data discrepancies, reporting breaks, and system issues
• Work with stakeholders to resolve root causes of operational and data errors
• Support testing and validation of system enhancements before release
• Assist with User Acceptance Testing (UAT) for operational system upgrades or enhancements
• Communicate clearly with business users on issue status and resolution timelines, * CI/CD pipelines and automated deployment for data engineering workloads
• Git-based source control, branching, pull requests, and release workflows via Azure DevOps and/or GitHub
• Azure Key Vault, managed identities, and RBAC for secure data access

Do you have experience in Communication skills?, Core Azure Platform

• Azure Data Factory, Azure SQL, Azure Synapse Analytics, Azure Data Lake Storage, Azure Databricks
• Cloud-native ELT/ETL pipeline design and implementation

Data Architecture & Modeling

• Datamart/lakehouse architecture, multi-layer ELT design
• Dimensional modeling: star schemas, facts, dimensions, and analytical data structures
• Data models for reporting, analytics, and downstream consumption layers, * Strong understanding of available data platforms (on-prem and cloud) with ability to right-fit technology to business need
• Experience with 3rd party Enterprise Data Management systems (Markit EDM, Asset Control, Golden Source, or similar)
• Deep knowledge of buy-side asset management data flows is a strong plus
• Ability to work in a fast-paced, agile environment managing multiple priorities simultaneously
• Strong written and verbal communication skills, * AI-aware mindset with the ability to identify opportunities to embed intelligent automation within data pipelines and architecture
• Experience applying AI to data quality use cases such as anomaly detection, exception handling, and automated reconciliation
• Familiarity with LLM-based tooling (e.g., GitHub Copilot, ChatGPT, Claude) to accelerate data engineering and architecture delivery
• Understanding of responsible AI principles, governance, and compliance considerations in a regulated financial services environment, * Experience with fixed income data domains including security master, pricing, analytics, benchmarks, or portfolio master
• Background in BI reporting and data model design for enterprise reporting layers, * Bachelor's degree in Computer Science, Information Systems, Finance, Mathematics, Engineering, or related field - or equivalent practical experience.
• 10+ years of relevant experience is required.

Pulled from the full job description

• Referral program
• Tuition reimbursement
• Health insurance
• Paid time off
• Vision insurance
• Dental insurance
• Life insurance, * Hybrid work environment
• Medical, dental, vision, and life insurance
• 401(k) with safe harbor (3%) and discretionary company contribution (12%)
• Tuition reimbursement up to $15,000 per year
• $5,000 employee referral bonus
• Business-casual environment (including jeans)
• Generous paid time off and leave programs
• Fitness, health, and composting reimbursements
• Eligibility for discretionary bonus program

Compensation is based on experience, skill set, and business needs.

Base Salary Range: $180,000-200,000

Income Research + Management is a Boston-based, privately owned, fixed income asset management firm. IR+M delivers strong performance and consistent results through a rigorous, bottom-up security selection process and strives to provide best-in-class client service to our 800+ institutional and private wealth clients. Founded in 1987 and located in the heart of Boston's financial district, IR+M employs 200 full time professionals and currently manages $135+ Billion in assets. We offer industry-leading benefits, as well as a challenging, collegial, and rewarding workplace with high levels of employee engagement.