Data and Analytics Engineer

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Job Summary

We are seeking a data-driven professional to join our DWCS (Digital Workplace and Client Services) Data and Analytics team. In this role, you will be responsible for transforming complex data into clear, actionable insights. You will develop and manage key metrics, automated data pipelines, and interactive dashboards that provide visibility into the effectiveness of our access control environment, helping to identify security risks and drive strategic improvements.

Key Responsibilities

• Develop & Maintain Metrics: Design, build, and maintain Key Performance Indicators (KPIs), operational reports, and dashboards to monitor the health, compliance, and effectiveness of DWCS services.

• Data Analysis & Anomaly Detection: Analyze large, multi-source datasets to identify trends, patterns, anomalies, and potential security risks related to user access, entitlements, client services and privileged accounts.

• Reporting & Visualization: Create compelling, interactive data visualizations and present analytical findings to stakeholders and leadership to support data-driven decision-making.

• Advanced Analytics, Predictive Modeling & AI Integration: Responsible for developing, validating, and applying statistical models, predictive analytics, and Generative/Agentic AI workflows to enhance analytical capabilities, automate complex data reasoning, and deliver forward-looking security intelligence.

• Ad-Hoc Analysis & Decision Support: Perform exploratory and ad-hoc data analyses across multi-source DWCS datasets to address urgent security/operational queries and deliver actionable insights for leadership.

• Data Engineering & Pipeline Maintenance: Build, maintain, and optimize batch and real-time ETL/ELT pipelines, SQL queries, and automated data refresh processes to ensure clean, reliable, and timely data feeds for BI and reporting platforms.

• Collaboration: Partner with operations, engineering, cybersecurity, and governance teams to understand their data requirements and deliver ongoing analytical support.

• Process Improvement & Data Integrity: Identify opportunities to automate reporting processes, establish data quality frameworks, and enhance data integrity across source systems.

Qualifications and Competencies: -

Basic Qualifications

• Experience: 5–8 years of relevant experience in data analytics, business intelligence, or data engineering.

• Data Analysis & Tools: Strong proficiency with data analysis and scripting tools such as SQL, Python, and Excel.

• Data Engineering: Proven experience in building and optimizing ETL/ELT data pipelines, managing batch/real-time data ingestion, and writing complex SQL queries for large, multi-source datasets.

• Data Visualization: Hands-on expertise with enterprise data visualization tools such as Tableau.

• Core Skills: Excellent analytical, problem-solving, and written/verbal communication skills.

Preferred Qualifications

• Advanced Analytics & AI (Preferred): Familiarity with statistical/predictive modeling (forecasting, regression), Generative AI (LLMs, RAG), and Agentic AI frameworks (e.g., LangGraph, CrewAI, tool-calling) to automate data reasoning and analytics workflows.

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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.