Investment / Asset Management Data Engineer

Bridgenext; Boston (MA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Bridgenext seeks an Investment Data Engineer in the Greater Boston area. You will design and maintain data pipelines for investment data domains, ingest Bloomberg feeds, and partner with investment and risk teams to align data with business needs.

You will contribute to a multi-year data ecosystem roadmap, focusing on data quality and scalability in a hybrid work environment with office visits 2–3 times per week.

Qualifications

• Strong hands-on data engineering / data pipeline development (ETL/ELT, orchestration, data modeling).
• Background with investment / asset management data, not just financial services.
• Experience with both public markets and private markets data.
• Understanding of hedge fund and/or investment product structures.
• Practical experience with Bloomberg data feeds (terminal data or reference data).
• Knowledge of investment-data structures and flows within the enterprise.
• Databricks or equivalent modern data platform experience.

Responsibilities

• Design, build, and maintain data pipelines for core investment data domains (Holding, Security, Relationship, Transaction).
• Ingest and transform Bloomberg and other market data feeds; ensure accurate downstream availability.
• Collaborate with investment, risk, and technology stakeholders to translate requirements.
• Contribute to the ongoing build-out of the target-state data ecosystem on a multi-year roadmap.
• Support analytics use cases, with focus on Fixed Income data.
• Build and optimize pipelines on Databricks with focus on scalability and data quality.

Skills

Data engineering

ETL/ELT

Data pipelines

Investment data

Bloomberg data

Databricks

Data modeling

Public markets

Private markets

Hedge funds

Tools

Databricks

Job description

Company Overview

At Bridgenext, we engineer Growth Operating Systems. Most enterprises have spent millions on their revenue stack and still aren't seeing the growth they expected.They have tools that function, but no system that wins. We help growth-hungry companies close that gap by turning fragmented platforms, siloed teams, and disconnected data into one integrated Growth OS. More than a technology company or marketing agency, we're a global digital consultancy with experts in engineering, data, AI, creative and more.

Our teams are made up of experts who believe in engineering impact, starting with putting people at the center of everything we do. Every team member directly shapes our work, culture, and values. Nothing matters more to us than a kind, respectful, fulfilling environment that supports everyone. Our flexible, inclusive culture gives you the autonomy, resources, and opportunities to thrive.

Position Description

Our client, a global asset management firm, is building toward a multi-year, target-state investment data ecosystem spanning Holding Master, Security Master (public and private markets), Relationship Master, Transaction Master, and Bloomberg/restricted product data. We are looking for a hybrid Investment Data Engineer who combines strong data engineering fundamentals with genuine fluency in investment/asset management data — someone who understands not just how to move and transform data, but what the data means and how it is consumed by the business. This is not a generic data engineering role; deep familiarity with investment products, market data structures, and asset management workflows is essential.

Key Responsibilities:

• Design, build, and maintain data pipelines supporting core investment data domains (Holding, Security, Relationship, and Transaction data) across public and private markets.
• Work with Bloomberg and other market data feeds, including restricted product data, ensuring accurate ingestion, transformation, and downstream availability.
• Partner with investment, risk, and technology stakeholders to translate business requirements into robust, well-modeled data pipelines.
• Contribute to the ongoing build-out of the target-state data ecosystem as part of a multi-year roadmap, not a one-time implementation.
• Support analytics use cases, with particular attention to Fixed Income data and analytics.
• Build and optimize pipelines on Databricks (or comparable modern data platform), applying engineering best practices for scalability, reliability, and data quality.
• Collaborate with data architects and SMEs to ensure pipeline design aligns with investment data structures and consumption patterns across the firm.

Practice Area:Data Engineering — Asset Management

Workplace: This role is hybrid and open to candidates in the Greater Boston area who are willing to travel to the office 2-3 times per week.

Must Have Skills:

• Strong hands-on data engineering / data pipeline development experience (ETL/ELT, orchestration, data modeling).
• Demonstrated background working with investment/asset management data — not just financial services generally.
• Exposure to both public markets and private markets data.
• Understanding of hedge fund and/or broader investment product structures.
• Practical experience with Bloomberg data (feeds, terminal data, reference data, or similar).
• Solid grasp of investment-data structures and flows (how holdings, securities, transactions, and relationships connect and move through the enterprise).
• Databricks or equivalent modern data platform experience highly desirable.

Preferred Skills:

• CFA designation (full or partial) or other meaningful investment-domain credentials/knowledge.
• Prior experience supporting a data platform modernization or target-state data architecture initiative in asset management.
• Familiarity with Fixed Income analytics.

What Success Looks Like:

A candidate who can sit between the data engineering team and the investment business, understand the "why" behind the data model, and build pipelines that reflect genuine domain understanding rather than purely technical execution.

Bridgenext is an Equal Opportunity Employer

US citizens and those authorized to work in the USA are encouraged to apply

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