Research Product Sr Associate - C11 - MUMBAI

Role Overview: The Data Engineer is a developing professional role within the Innovation Lab. Deals with most data engineering, database development, and pipeline problems independently and has some latitude to solve complex data integration and processing issues. Integrates in-depth specialty knowledge of database management, SQL, and Python-based data processing frameworks with a solid understanding of software industry standards and practices. Good understanding of how the development and data team integrates with others in accomplishing the objectives of the subfunction/ job family. Applies analytical thinking and knowledge of data pipeline orchestration, database systems, and modern data engineering methodologies. Requires attention to detail when making judgments and recommendations based on the analysis of factual and relational data. Typically deals with variable and complex database issues with potentially broader business impact. Applies professional judgment when designing, optimizing, and interpreting data structures, pipelines, and results. Breaks down information and data architectures in a systematic and communicable manner. Developed communication and diplomacy skills are required in order to exchange potentially complex/sensitive technical information with product managers, developers, and global stakeholders. Moderate but direct impact through close contact with the businesses' core activities. Quality and timeliness of data pipeline services provided will affect the effectiveness of own team and other closely related analyst teams.

Responsibilities:

• Collaborate with Product Managers to formulate Data Engineering projects and analyze complex data requirements.
• Design, develop, and maintain automated, scalable data pipelines (ETL/ELT) and data ingestion workflows using Python and SQL.
• Deliver optimized data pipeline solutions and propose new data acquisition and automated curation opportunities that directly impact key initiatives across the department.
• Act as a point of contact for queries from the department relating to data architecture, ETL processes, and database objects.
• Manage multiple development initiatives and prioritize tasks with varying levels of urgency simultaneously in an aggressive, Agile-based development environment.
• Part of a truly global team (strategically located in New York and Mumbai) with very experienced, yet collegial, stakeholders who will hold you to an exceptionally high standard.
• Participate in testing and validation of data flows, database scripts, and ETL transformations prior to deployments to ensure the accuracy, timeliness, and completeness of data.
• Utilize modern AI/LLM-based productivity tools to accelerate development workflows, debug code, optimize database queries, and document datasets.
• Understand the Citi Research business and its drivers, aligning data workflows with financial research goals.
• Perform less structured (scripted), ad-hoc tasks as necessary, summarizing steps taken and results achieved for Management (e.g., writing custom Python data-profiling scripts, leveraging LLMs to aid in fast text extraction, or running complex Excel/VBA reporting).
• 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:

• Exceptional attention to detail in database design, data validation, and pipeline construction.
• Excellent written and verbal communication skills to effectively gather requirements and collaborate with Product Managers and Development Leads.
• Ability to execute and thrive in a large, matrixed, and global organization.
• Self-starter with the ability to solve complex database and data integration problems independently.
• Outstanding track record of delivering high-quality work in an aggressive, Agile-based development environment, including familiarity with JIRA for task tracking, user story scoping, and effort estimation.
• 5-7 years of minimum relevant experience as a Data Engineer.
• High proficiency in Python (including pandas, NumPy, and standard data libraries) and SQL (Oracle, SQL Server, or PostgreSQL).
• Experience building data pipelines using ETL tools (such as Talend, SSIS, or custom Python-based ETL processes).
• Working knowledge of productivity enhancements brought by Large Language Models (LLMs) and Generative AI (e.g., leveraging AI assistants for efficient code generation, scripting optimization, SQL writing, and routine development task automation).
• Advanced proficiency in Microsoft Excel (e.g., VLOOKUP, pivot tables, and minor VBA knowledge).
• Familiarity with containerization (Docker or Podman) and SCM (Git/GitHub) is preferred.

Education:

• Recognized Bachelor’s/Master’s degree in Science, Computers, Engineering, or equivalent experience.

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

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