Technical Business Systems Analyst

Job Summary

One of our leading client is looking for Technical Business Systems Analyst in Newark NJ

• Capital markets (Equity, Fixed Income, Derivatives)
• Asset allocation and risk-adjusted returns
• CFA (Chartered Financial Analyst) – Required or Progressing
• Data analysis and reporting tools (SQL, Power BI, Tableau)
• Experience with financial platforms or data sources (Bloomberg, Fact Set, etc.)
• Requirement gathering and documentation
• Process mapping and workflow design
• Strong analytical and problem-solving skills
• Own end to end delivery and support of financial services data products, from requirement intake through production support, ensuring stability, accuracy, and timeliness.
• Act as the primary Technical BSA for BAU and production data issues, taking accountability for root cause analysis, remediation, and prevention of recurring issues.
• Partner with business stakeholders to translate financial domain business needs into clear, actionable functional and technical specifications, including data mappings, transformations, and validation rules.
• Work closely with data engineering and technology teams to analyze existing data logic, review SQL and code, and validate that implementations align with business intent.
• Proactively monitor and assess data quality, identify issues early, and drive resolution through to completion rather than simple escalation.
• Support Agile delivery by contributing to backlog refinement, sprint planning, story breakdown, acceptance criteria, and release readiness.
• Collaborate with Front Office, Risk, Operations, and downstream consumers to clarify requirements, resolve data questions, and ensure shared understanding of outputs and impacts.
• Ensure data solutions meet production grade standards, including stability, accuracy, traceability, auditability, and operational resilience.
• Continuously improve BAU processes, controls, and documentation, reducing operational risk and improving transparency and efficiency.
• Proactively identify opportunities for process optimisation, automation, and improved data controls, incorporating best practices across financial services data delivery.

Essential skills/knowledge/experience:

• Bachelor’s degree in computer science, Information Systems, Data Analytics, Business Information Systems, or a related discipline.
• 5+ years proven experience in a Technical Business Analyst, Business Systems Analyst, Data Analyst, or similar role within financial services / capital markets.
• Hands on experience supporting investment, trading, risk, operations, or regulatory reporting data platforms in a production environment.
• Experience working with industry standard investment or portfolio management platforms.
• Strong understanding of financial services data domains, with the ability to engage confidently with Front Office, Risk, Operations, and Technology stakeholders without heavy translation layers.
• Demonstrated experience acting as a primary BA/BSA for BAU and production critical issues, with clear ownership from investigation through resolution.
• Strong analytical and problem solving skills, particularly in the context of complex data, business logic, and operational issues.
• Excellent communication skills, with the ability to explain complex data concepts clearly to both technical and non technical audiences.
• Ability to manage multiple priorities and deliver outcomes in a fast paced, Agile delivery environment, with a strong sense of ownership and accountability.

• Strong SQL expertise, including the ability to:
• write, review, and optimise complex queries,
• perform independent data analysis and validation
• debug and investigate production data issues
• Hands on experience working with relational data models and enterprise data platforms (e.g. Microsoft SQL Server).
• Ability to read existing code (e.g. SQL, Python, Java) to extract, decompose, and validate underlying business logic.
• Solid understanding of core data concepts, including:
• Source to target mappings
• Data transformations and enrichment
• Historical vs “as of” data handling
• Data quality, reconciliation, and control frameworks
• Good understanding of data flows, system integrations, and application architectures within enterprise environments.
• Exposure to process optimisation, automation, or data governance initiatives within financial services.
• Experience working in globally distributed delivery teams.