About the Role
We are seeking an experienced Senior Business Analyst to support large-scale data platforms focused on ingesting, processing, managing, and analyzing securities trading data.
The ideal candidate will act as a bridge between business stakeholders, data engineering, QA, and analytics teams, translating complex business and regulatory requirements into clear, actionable technical specifications. The role involves working on data pipelines, data quality controls, data governance, lineage, and analytics capabilities supporting market surveillance and regulatory oversight.
Key Responsibilities
- Translate business requirements into detailed functional specifications, user stories, and measurable acceptance criteria.
- Document and validate end-to-end ETL/ELT data pipelines, including source systems, transformation logic, loading processes, and downstream data consumers.
- Define requirements for data pipeline enhancements, schema changes, new data feeds, and data reprocessing.
- Establish and monitor data quality rules covering completeness, accuracy, consistency, and timeliness.
- Maintain data lineage and traceability documentation to ensure data outputs can be traced back to their source records.
- Define business rules for handling late, missing, duplicate, corrected, and cancelled records, including reprocessing and audit requirements.
- Collaborate with data engineers, QA, and analytics teams on data platform architecture and technology decisions.
- Plan and support User Acceptance Testing (UAT), data validation, and test scenario development for pipeline and business rule changes.
- Manage stakeholder expectations, requirements prioritization, impact analysis, scope, and change control.
- Analyze business and data requirements, present findings, and provide recommendations to senior stakeholders.
Required Qualifications
- 8+ years of experience as a Business Analyst or Data Analyst on data-intensive projects, preferably involving data engineering or enterprise data platforms.
- Hands-on experience documenting, analyzing, or testing ETL/ELT data pipelines.
- Strong SQL skills for data profiling, reconciliation, validation, and analysis.
- Good understanding of Data Lake and Data Warehouse architectures.
- Knowledge of data storage formats such as Parquet and CSV, including schema evolution, compression, and query performance.
- Experience with data quality, data governance, and data lineage concepts.
- Strong experience in requirements gathering, functional documentation, user stories, acceptance criteria, process flows, and data flow modeling.
- Experience working with cross-functional teams, including business stakeholders, data engineers, QA, and analytics teams.
- Familiarity with cloud-based data platforms, preferably AWS.
- Experience with Agile methodologies and tools such as Jira and Confluence.
- Excellent communication, analytical, problem-solving, and stakeholder management skills.
Preferred Qualifications
- Experience in the capital markets or financial services domain.
- Understanding of the order and trade lifecycle, including order entry, routing, execution, allocation, clearing, and settlement.
- Knowledge of trade amendments, cancellations, and corrections.
- Familiarity with regulatory market surveillance and trading manipulation patterns, including spoofing, layering, wash trades, and front-running.
- Understanding of timestamp precision and clock synchronization in market data processing, event sequencing, and order book reconstruction.
- Experience with data catalog, data lineage, surveillance, or compliance analytics tools.
- Exposure to Agile delivery environments and large-scale data transformation initiatives.