Data Ops Capability Deployment - Analyst - AVP, C12 - Banking & International, Pune

Data Ops Capability Deployment - Analyst is a seasoned professional role. Applies in-depth disciplinary knowledge, contributing to the development of new solutions/frameworks/techniques and the improvement of processes and workflow for Enterprise Data function. Integrates subject matter and industry expertise within a defined area. Requires in-depth understanding of how areas collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the function and overall business.

The primary purpose of this role is to perform data analytics and data analysis across different asset classes, and to build data science/Tooling capabilities within the team. This will involve working closely with the wider Enterprise Data team, in particular the front to back leads to deliver business priorities.

The following role is within B & I Data Capabilities team within the Enterprise Data. The team manages the Data quality/Metrics/Controls program in addition to a broad remit to implement and embed improved data governance and data management practices throughout the region. The Data quality program is centered on enhancing Citi’s approach to data risk and addressing regulatory commitments in this area.

Key Responsibilities:

• Hands on with data engineering background and have thorough understanding of Distributed Data platforms and Cloud services.
• Sound understanding of data architecture and data integration with enterprise applications
• Research and evaluate new data technologies, data mesh architecture and self-service data platforms
• Work closely with Enterprise Architecture Team on the definition and refinement of overall data strategy
• Should be able to address performance bottlenecks, design batch orchestrations, and deliver Reporting capabilities.
• Ability to perform complex data analytics (data cleansing, transformation, joins, aggregation etc.) on large complex datasets.
• Build analytics dashboards & data science capabilities for Enterprise Data platforms.
• Communicate complicated findings and propose solutions to a variety of stakeholders.
• Understanding business and functional requirements provided by business analysts and convert into technical design documents.
• Work closely with cross-functional teams e.g. Business Analysis, Product Assurance, Platforms and Infrastructure, Business Office, Control and Production Support. Prepare handover documents and manage SIT, UAT and Implementation.
• Demonstrate an in-depth understanding of how the development function integrates within overall business/technology to achieve objectives; requires a good understanding of the banking industry.
• Performs other duties and functions as assigned.
• 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.

Skills & Qualifications

10 + years of active development background and experience in Financial Services or Finance IT is a required.

• Experience with Data Quality/Data Tracing/Data Lineage/Metadata Management Tools
• Hands on experience for ETL using PySpark on distributed platforms along with data ingestion, Spark optimization, resource utilization, capacity planning & batch orchestration.
• In depth understanding of Hive, HDFS, Airflow, job scheduler
• Strong programming skills in Python with experience in data manipulation and analysis libraries (Pandas, Numpy)
• Should be able to write complex SQL/Stored Procs
• Should have worked on DevOps, Jenkins/Lightspeed, Git, CoPilot.
• Strong knowledge in one or more of the BI visualization tools such as Tableau, PowerBI.
• Proven experience in implementing Datalake/Datawarehouse for enterprise use cases.
• Exposure to analytical tools and AI/ML is desired.

Education:

• Bachelor's/University degree, master's degree in information systems, Business Analysis / Computer Science.

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