Responsibilities:
- Integrates subject matter and industry expertise within a defined area.
- Contributes to data analytics standards around which others will operate.
- Applies in-depth understanding of how data analytics collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the entire function.
- Employs developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers.
- Resolves occasionally complex and highly variable issues.
- Produces detailed analysis of issues where the best course of action is not evident from the information available, but actions must be recommended/ taken.
- Responsible for volume, quality, timeliness and delivery of data science projects along with short-term planning resource planning.
- 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:
10+ years of progressive experience in the IT field, with a focus on data engineering and analytics.
• 8+ years of hands-on experience working with Hadoop and other big data technologies.
• 8+ years of experience in Python programming with expertise in automation testing to design, develop, and automate robust software solutions and testing frameworks.
• 8+ years of experience in designing, developing, and implementing complex data pipelines for data ingestion, transformation, and processing using PySpark and Python.
• 8+ years of experience in designing, developing, and implementing complex data pipelines for data ingestion, transformation, and processing using SAS and other ETL Tools like Ab Initio/ Data Stage.
• 8+ years of experience in designing, developing, and implementing complex data pipelines for scheduling.
• Experience in modernizing legacy pipelines by converting them to big data technologies, ensuring improved scalability and performance.
• 5+ years of experience leading large-scale data and analytics projects, with demonstrated ability to manage all aspects of the project lifecycle, from initiation to delivery.
• Familiarity with CI/CD practices and automation tools to streamline development, test automation and deployment processes.
• Proven experience in team leadership, including mentoring and guiding technical teams to achieve project goals.
• Industry experience within banking, capital markets, or the broader financial services sector is strongly preferred.
• Hands-on experience with enterprise-scale, multi-region projects, showcasing the ability to work in complex, distributed environments.
- Education:
- Bachelor’s/University degree or equivalent experience, potentially Masters degree