Investments Data Platform Analyst

Job Title: Technical Business Analyst – Investments Data Platform
Location: Holmdel, NJ (Hybrid)

Technical Business Analyst (TBA) to support our Investments Data Platform initiatives. This role partners closely with Product Manager/Product Owner, and business stakeholders to capture, analyze, and translate complex investment data requirements into scalable technology solutions.
The ideal candidate will have hands-on experience working with investment data (holdings, trades, securities, ratings, cash flows) and will play a key role in driving data integration, automation, and reporting capabilities across the platform.

Required Qualifications
    Bachelor’s degree in Finance, Computer Science, Information Systems, or related field
    5+ years of experience as a Technical Business Analyst in investment, asset management, or financial services domain
    Strong understanding of investment data concepts (e.g., securities, trades, portfolios, asset classes, ratings)
    Hands-on experience with Jira (features, epics, user stories, backlog management)
    Strong data analysis skills using SQL, Excel, or similar tools
    Experience working in Agile/Scrum delivery environments

Preferred Qualifications
    Experience with investment data platforms, data lakes, or warehouse architectures
    Familiarity with tools such as Neoxam data hub, Databricks, Python, or cloud data platforms (Azure/AWS)
    Experience with data ingestion frameworks, ETL/ELT pipelines, and API integrations
    Knowledge of private placements, fixed income, or insurance investment portfolios
    Exposure to enterprise platforms

 Key Responsibilities
Investment Data Requirements & Analysis
    Collaborate with Product Manager/Product Owner, portfolio teams, risk, and operations stakeholders to gather and document business requirements
    Translate investment workflows into functional specifications, data mappings, and system requirements
    Analyze datasets such as holdings, trades, issuer/security master, pricing, and ratings data to support solution design
    Understand upstream/downstream dependencies across data pipelines and reporting systems

Data Analysis & Data Quality
    Perform detailed data profiling, reconciliation, and validation across multiple systems (e.g., source files, data platforms, reporting tools)
    Identify and resolve data quality issues, breaks, and inconsistencies
    Define and document business rules, transformations, and validation checks
    Support data lineage and traceability across ingestion to consumption layers
- Jira, Agile Delivery & Backlog Management
- Requirement Refinement & Cross-Team Collaboration
- Testing & UAT (User Acceptance Testing)