Top Data & Analytics Jobs

Leads product analytics for Retail Bank growth, using SQL, Python, R, experimentation, causal inference, statistical modeling, segmentation, and data storytelling. Partners with Product, Engineering, Finance, and Research to shape roadmaps, prioritize opportunities, establish KPI standards, and influence investment and product decisions.

Leads people analytics initiatives that support talent strategy and workforce decisions. Responsibilities include developing analytics frameworks, managing data projects, building AI-powered data products and self-service tools, analyzing workforce data, prototyping automation solutions, and delivering insights to HR stakeholders and senior leaders. The role also involves data strategy, dashboard development, project execution, and potentially people management.

Leads enterprise analytical-tool validation, including framework refinement, project execution, methodology risk assessment, technical research, prototyping, and validation reporting. Partners with cross-functional leaders to influence business strategy, solves complex analytical problems, and coaches junior staff. Requires substantial data analytics, open-source technology, statistical modeling, and people-management experience.

Leads enterprise data risk measurement and analytics by defining metrics, building dashboards and data products, monitoring trends, translating policies into actionable insights, and presenting recommendations to executives. Manages junior analysts, drives cross-functional initiatives, supports data governance, applies AI to automate metrics, and performs analysis across large databases to improve processes, reporting, and business outcomes.

Build and operate scalable cloud data platforms, pipelines, and applications using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Design data models, enforce engineering patterns and security standards, support distributed and streaming workloads, and deliver resilient solutions. Collaborate with product managers, software engineers, analysts, and data scientists while mentoring teammates and communicating technical concepts to stakeholders.

Performs data analysis, business intelligence, data management, and data quality work. Builds data solutions, dashboards, metrics, and self-service tools; analyzes complex datasets; partners with business and technology teams; manages metadata, lineage, access governance, and data quality monitoring. Requires quantitative education and experience with scripting, visualization, data querying, Snowflake, and related analytics platforms.

Designs, builds, and operates scalable cloud data pipelines, platforms, and applications. Responsibilities include distributed data processing, data modeling, relational and NoSQL database development, data security, observability, orchestration, and data warehousing. The role collaborates with engineering, analytics, product, and data science teams; establishes reusable engineering patterns; communicates technical concepts; and mentors data professionals.

Design, build, and operate scalable cloud data platforms, pipelines, and applications. Develop distributed, real-time, and warehouse solutions using Python, Spark, SQL, Databricks, Snowflake, and relational or NoSQL databases. Apply data security, encryption, access controls, observability, and reusable engineering patterns. Collaborate with product managers, engineers, analysts, and data scientists while mentoring team members and communicating technical outcomes to stakeholders.

Build and operate scalable cloud data pipelines, platforms, and applications for risk management. Design data architectures, enforce engineering standards, implement security controls, and work with distributed data, AI, microservices, lakehouse systems, and relational and NoSQL databases. Collaborate across Agile teams, mentor data professionals, communicate technical outcomes, and deliver resilient solutions using technologies such as Python, Spark, Databricks, Snowflake, and cloud platforms.

Design, build, and operate scalable cloud data platforms, pipelines, and applications. Collaborate with data scientists, analysts, engineers, and product managers while applying distributed computing, lakehouse architecture, data modeling, security, and observability practices. Develop resilient relational and NoSQL data solutions, mentor team members, enforce engineering standards, and communicate technical outcomes to stakeholders. The role requires independent delivery of cloud-first data products supporting large-scale financial experiences.