Top Data & Analytics Jobs

The Data & AI Engineer III will lead cloud data engineering solutions, develop data infrastructure, establish architectures, mentor team members, and secure data around cloud systems.

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Own and govern centralized data assets; design scalable dbt/Snowflake models; model Stripe subscription and payments data; set SQL standards, testing, monitoring and documentation; lead complex BI projects in Hex; partner with product, engineering, operations and GTM to deliver durable analytics solutions.

Collects, cleans, validates, analyzes, and interprets data to support business decisions. Develops reports, dashboards, presentations, and performance measurements; identifies trends; and translates complex information into actionable recommendations. Collaborates with technical and non-technical stakeholders, communicates findings clearly, maintains data accuracy, and supports multiple analytics projects and deadlines.

Collects and analyzes business data, develops dashboards and reports, monitors KPIs, identifies trends, verifies data accuracy, and provides insights to support forecasting, planning, and informed decision-making. Collaborates with departments and technical teams to understand reporting needs, improve data processes, communicate findings clearly, and recommend business improvements.

Build and own production data infrastructure for a healthcare AI platform. Responsibilities include REST API ingestion, Azure Event Hubs streaming into Databricks, Delta Lake medallion pipelines, entity resolution, semantic metrics, data-quality instrumentation, reconciliation, schema-drift handling, and troubleshooting source-to-warehouse discrepancies. The role requires strong Python and SQL skills, independent pipeline ownership, and experience with Databricks, Spark, PySpark, streaming, and healthcare-related data is a plus.

Builds and leads scalable big data pipelines, ETL processes, data models, integrations, and governance solutions. The role develops and tests code using Scala, Python, Spark, and SQL; orchestrates cloud-based workflows; ensures data quality, documentation, reliability, and disaster recovery; and provides architectural guidance and mentorship. It also partners with business stakeholders to translate complex problems into data solutions and delivers dashboards, insights, and operational improvements.

Build and maintain data integration infrastructure, pipelines, data models, governance practices, and scalable analytical solutions. Translate business problems into data-driven solutions, identify and transform complex data sources, develop and test code, support production applications, and guide junior team members. Collaborate with stakeholders on business cases, data strategy, quality, architecture, documentation, and governance while applying modern distributed technologies and software engineering best practices.

Leads marketing performance analytics across media, CRM, digital, ecommerce, customer behavior, and business outcomes. Translates complex data into executive-ready insights, recommendations, and investment decisions. Defines KPIs, measurement frameworks, dashboards, and reporting standards; evaluates incrementality, attribution, lift, and marketing mix models. Partners with Marketing, Finance, Digital, Brand, and Business Intelligence teams while managing and developing analytical talent.

Lead consumer insights and market research initiatives supporting Citi’s credit card business, product development, marketing communications, and customer experience. Manage qualitative, quantitative, and mixed-method research from objectives through analysis and reporting; translate findings into actionable business recommendations; present insights to senior leaders; and coordinate vendors, agencies, budgets, timelines, compliance, and multiple internal partners.