IT - Technical Business Analyst - Investments Data Platform

Position:
Technical Business Analyst
-1

Duration: 7+ months contract-to-hire role

Location:

Holmdel, NJ 07733 - Hybrid (Wed & Thurs)

We are seeking a highly analytical and detail-oriented 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.

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

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

Create and manage Jira features, epics, and user stories aligned to investment data initiatives

Break down requirements into granular, testable stories with clear acceptance criteria

Participate in backlog refinement, planning, and prioritization with Product and Engineering teams

Ensure traceability between business requirements, technical design, and delivery artifacts

Continuously refine requirements through iteration, stakeholder feedback, and technical feasibility discussions

Collaborate with data engineers, platform teams, and architects to ensure alignment with system design

Work closely with QA teams to define test scenarios and ensure requirements are correctly implemented

Act as a bridge between business and technical teams, ensuring shared understanding

Define and execute UAT test cases aligned with investment workflows and data outputs

Validate end-to-end flows (e.g., data ingestion transformation reporting)

Coordinate with business users to ensure functional completeness and accuracy

Log and track defects, and support resolution through to closure

Provide regular updates on feature progress, risks, and dependencies

Support release validation and production rollout activities

Ensure delivered solutions meet business expectations and data accuracy standards

Contribute to continuous improvement of data platform processes and automation

Bachelors 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

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

Strong analytical and data problem-solving skills

Deep understanding of data flows, transformations, and integrations

Excellent stakeholder management and communication

Ability to translate complex business problems into scalable data solutions

High attention to detail with focus on data accuracy and completeness

High-quality data-driven user stories with clear acceptance criteria

Reduced data defects and reconciliation breaks

Timely delivery of investment data features and platform enhancements

Improved data quality, lineage visibility, and operational efficiency

Strong stakeholder satisfaction across business, product, and engineering teams