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Vice President, Data Architect, Data Service and Governance

Job in Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: Income Research + Management
Full Time position
Listed on 2026-06-26
Job specializations:
  • IT/Tech
    Data Engineering, Azure
Salary/Wage Range or Industry Benchmark: 180000 - 200000 USD Yearly USD 180000.00 200000.00 YEAR
Job Description & How to Apply Below

Income Research + Management

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.

Open Position

VP, Data Architect, Data Service and Governance

Overview

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
Leadership & Collaboration
  • 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
  • Participate 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
Required Skills Experience 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
Dev Ops & Engineering Practices
  • CI/CD pipelines and automated deployment for data engineering workloads
  • Git‑based source control, branching, pull requests, and release workflows via Azure Dev Ops and/or Git Hub
  • Azure Key Vault, managed identities, and RBAC for secure data access
Platform & Domain Knowledge
  • Strong understanding of available data platforms (on‑prem and cloud) with ability to right‑fit…
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