IT - Technical Business Analyst - Investments Data Platform

Position: Technical Business Analyst ID: 1001-1

Duration: 7+ months contract-to-hire role

Location: Holmdel, NJ 07733 - Hybrid (Wed & Thurs)

Job Summary:

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.

Key Responsibilities:

Requirements

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

• 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

• 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

• 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