Description

Key Skills: SQL, Python, Data Analysis, Big Data, Hadoop, Spark, Databricks, Tableau, Power BI, Data Modeling

Good to Have Skills: Experience with regulatory reporting (Basel, CCAR, FR 2052a) and liquidity risk management. Proficiency in R programming, AWS S3 cloud platforms, QlikView visualization, and machine learning model development. Knowledge of data warehousing concepts including dimensional modeling and star/snowflake schemas. Experience with relational databases such as Oracle, SQL Server, and DB2. Understanding of Software Development Life Cycle (SDLC) with focus on data-centric projects and data governance frameworks.

Roles & Responsibilities:

• Consult with business clients to determine system functional specifications and partner with multiple management teams.
• Define, document, and validate detailed data requirements, data flows, and data lineage for new systems.
• Provide technical input during development and implementation phases for complex, high-impact projects.
• Design and develop robust data models to support reporting, analytics, and business processes.
• Prepare and curate data for AI/ML model development, working closely with AI engineers.
• Develop and maintain data visualization dashboards and reports translating complex data into business insights.
• Lead the analysis of complex data sets to identify trends, patterns, and anomalies.
• Identify and communicate data-related risks and impacts and propose risk mitigation options.
• Evaluate new data technologies, analytical tools, and evolving business requirements for system enhancements.
• Serve as advisor or coach to new or lower-level analysts within the organization.

Experience Required: 11+ years of experience as a Technical Data Analyst or similar role within the Financial Services industry, preferably in regulatory reporting and liquidity risk.

Education: Bachelor's degree or University degree or equivalent experience. Master's degree preferred

Key Skills

Education

Any Graduate