Lead Data Analyst – Enterprise Data Analytics
About The Position
Raymond James is seeking an experienced Lead Data Analyst to join its Enterprise Data Analytics team. The role delivers complex data analysis, reporting, and analytical solutions supporting business, operational, risk, compliance, and regulatory initiatives across the firm. The analyst collaborates with business stakeholders, technology teams, and enterprise data teams to translate complex requirements into accurate, scalable, actionable data solutions. The position leads complex analytical initiatives, provides technical guidance to other analysts, and contributes to data modernization, process automation, and adoption of emerging AI technologies. The ideal candidate has advanced SQL expertise, strong analytical and problem-solving skills, and experience working with large enterprise datasets across multiple systems. The workstyle is hybrid, with travel of less than 25%. The total compensation includes base salary or wages and may include additional compensation such as cash or equity, discretionary bonuses, or commissions. Benefits may include medical, dental, and vision coverage; life, critical illness, accident, and disability insurance; retirement savings; paid time off, including vacation, holidays, and sick leave; and parental leave. Eligibility and specific offerings may vary by position and employment status.
Requirements
- Bachelor's degree in Computer Science, Information Technology, Data Analytics, Information Systems, Finance, or a related field, or equivalent practical experience.
- 8–10 years of relevant experience in data analytics, business intelligence, enterprise data management, or related disciplines.
- Advanced hands-on SQL experience, including complex query development, optimization, and troubleshooting.
- Experience analyzing, reconciling, and validating large datasets across multiple systems.
- Experience with enterprise relational databases, data warehouses, or cloud-based analytics platforms.
- Strong analytical, problem-solving, and root cause analysis skills.
- Experience gathering business requirements and translating them into analytical solutions.
- Strong communication, stakeholder management, and technical documentation skills.
- Ability to lead complex analytical initiatives and provide technical guidance to other analysts.
Nice To Haves
- Experience in financial services, wealth management, brokerage, capital markets, risk management, or compliance.
- Knowledge of financial datasets, including customer accounts, securities transactions, positions, holdings, and balances.
- Experience with AWS technologies such as Amazon Redshift, S3, Athena, and Glue.
- Experience with ETL/ELT processes, data pipelines, data integration, and data modernization.
- Working knowledge of Python and pandas for data analysis, validation, scripting, and automation.
- Experience with Qlik Sense, Tableau, Power BI, or similar business intelligence platforms.
- Familiarity with data governance, data lineage, source-to-target mapping, and data quality frameworks.
- Experience supporting regulatory reporting, investigations, legal discovery, or audit-related data requests.
- Experience with AI-powered productivity tools such as Microsoft Copilot, ChatGPT, Claude, or similar approved technologies.
- Experience developing automated reporting, reusable queries, and analytical validation processes.
Responsibilities
- Lead complex data analysis and reporting initiatives for business, operational, risk, compliance, and regulatory needs.
- Gather stakeholder requirements, define scope, and translate business needs into technical data solutions.
- Extract, transform, reconcile, and validate data across multiple enterprise sources.
- Analyze large datasets to identify trends, investigate discrepancies, and provide actionable insights.
- Manage multiple high-priority analytical requests independently and deliver accurate results on time.
- Develop, optimize, and maintain complex SQL queries for data extraction, analysis, reconciliation, and reporting.
- Work with enterprise databases, data warehouses, cloud platforms, and legacy systems.
- Collaborate with enterprise data teams to understand data structures, business rules, lineage, and source-to-target mappings.
- Support data modernization, cloud adoption, and data integration initiatives.
- Develop and execute validation and reconciliation processes to ensure data accuracy, completeness, and consistency.
- Investigate data anomalies, perform root cause analysis, and recommend corrective actions.
- Establish reusable analytical methodologies, validation frameworks, and reporting standards.
- Handle confidential and sensitive data according to enterprise security and governance requirements.
- Serve as a technical subject matter expert in SQL development, data analysis, and troubleshooting.
- Provide technical guidance, review analytical solutions, and mentor other analysts.
- Partner with cross-functional teams to resolve complex data challenges.
- Identify opportunities to improve efficiency through automation, reusable solutions, and process standardization.
- Explore and use approved AI-powered tools for data analysis, SQL development, testing, documentation, and automation.
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Critical illness insurance
- Accident insurance
- Disability benefits
- Retirement savings
- Paid time off, including vacation, holidays, and sick leave
- Parental leave
- Compensation may include additional cash or equity, discretionary bonuses, or commissions
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What This Job Offers
Job Type
Full-time
Career Level
Senior
