Senior PySpark Python Data Engineer - Assistant Vice President

Job Description

Job Profile Name: Senior PySpark Python Data Engineer - Assistant Vice President- C12

Job Description:

The Technical Data Analyst is a senior-level position responsible for bridging the gap between complex business requirements and technical data solutions, leveraging advanced analytical and technical skills to develop data-driven solutions, with a focus on regulatory reporting and liquidity risk initiatives. This role will liaise extensively with business stakeholders and technology teams to articulate data needs, extract insights, and ensure data quality and integrity.

Responsibilities:

• Consult with business clients to determine system functional specifications and partner with multiple management teams and other units to meet organizational objectives.
• Define, document, and validate detailed data requirements, data flows, and data lineage for new or enhanced systems and applications.
• Provide technical input during the development and implementation phases, including formulating and defining systems scope, data objectives, and necessary data architecture enhancements for complex, high-impact projects.
• Design and develop robust data models (conceptual, logical, physical) to support reporting, analytics, and business processes.
• Prepare and curate data for AI/ML model development, working closely with AI engineers to ensure data quality, feature engineering, and model validation.
• Utilize advanced SQL for data extraction, manipulation, and analysis from various relational databases, data warehouses, and Big Data platforms.
• Develop and maintain data visualization dashboards and reports using tools such as Tableau, Power BI, or QlikView, translating complex data into understandable business insights.
• Lead the analysis of complex data sets to identify trends, patterns, and anomalies relevant to regulatory reporting, liquidity risk, and other critical financial functions.
• Identify and communicate data-related risks and impacts and propose risk mitigation options, considering business implications of the application of technology to the current business environment.
• Evaluate new data technologies, analytical tools, and evolving business requirements, and recommend appropriate systems alternatives and/or enhancements to current systems by analyzing business processes, systems and industry standards.
• Serve as advisor or coach to new or lower level analysts.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Qualifications:

• 8-12 years of experience as a Senior PySpark Python Data Engineer or similar role within the Financial Services industry, preferably in regulatory reporting (e.g., Basel, CCAR, FR 2052a) and liquidity risk.
• Advanced proficiency in PySpark, Python, SQL for complex data querying, analysis, and optimization across large datasets.
• Strong experience with relational databases (e.g., Oracle, SQL Server, DB2) and data warehousing concepts (e.g., dimensional modeling, star/snowflake schemas).
• Demonstrated expertise with Big Data technologies including Hadoop, Spark (PySpark/Scala Spark), Kafka, and cloud-based data platforms (e.g., AWS S3, Databricks).
• Demonstrated experience with data modeling tools and techniques.
• Proficiency in data visualization tools (e.g., Tableau, Power BI, QlikView) and strong Excel skills for data manipulation and presentation.
• Experience with scripting languages for data analysis (e.g., Python, R) is highly desirable.
• Experience with data preparation for AI/ML models and understanding of core AI/ML concepts and workflows is highly desirable.
• Comprehensive knowledge of data analysis principles, methodologies, and data governance frameworks.
• Experience across all phases of the Software Development Life Cycle (SDLC), with a focus on data-centric projects.
• Consistently demonstrates clear and concise written and verbal communication.
• Demonstrated problem-solving and decision-making skills.
• Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements.

Education:

• Bachelor's degree/University degree or equivalent experience.
• Master's degree preferred.

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