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Strong Tier-1 brand plus generic Business Analyst title, but senior and niche skills narrow candidate pool.
Strong financial data domain requirements and specific platform experience reduce cross-industry transferability.
Explicit 10+ years, 5+ years data integration, and required Snowflake/ETL skills make filters highly restrictive.
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Lead definition and documentation of business and technical requirements for enterprise cloud-based data integration, ETL/ELT modernization, and data warehousing initiatives.
Collaborate with cross-functional teams including business stakeholders, data architects, and engineering to deliver scalable, secure, and configurable data solutions across platforms like Snowflake, Azure, SQL Server, and Oracle.
Support Agile delivery activities such as sprint planning, backlog management, UAT, QA coordination, and production issue resolution to ensure high-quality data integration capabilities.
10+ years business analysis or systems analysis experience in software delivery or data platforms; 5+ years supporting enterprise data integration or data warehousing initiatives.
Strong financial services domain experience, especially with investment, market, reference data, or financial operations data.
Expertise in cloud data platforms (Snowflake preferred), relational databases (SQL Server, Oracle), ETL/ELT tools (e.g. Azure Data Factory, Talend, Informatica) and SQL query analysis.
Bachelor’s degree in Finance, Computer Science, Information Systems, Engineering, Mathematics, Data Science, Physics or related technical/quantitative field; advanced degree strongly preferred.
Experienced in translating complex financial data workflows into detailed functional specifications, source-to-target mappings, and acceptance criteria to bridge business and technical teams.
Proficient in Agile methodologies with strong capability managing Jira backlogs, facilitating scrum ceremonies, and coordinating globally distributed teams across product, engineering, QA, and operations.
Demonstrated strategic understanding of modern cloud data architectures, data governance, metadata-driven integration frameworks, and strong stakeholder management skills in a financial data modernization context.