Top Data & Analytics Jobs

Design, build, and support scalable cloud data pipelines, platforms, and applications using Python, Spark, AWS, Databricks, Snowflake, and related technologies. Develop data models and end-to-end solutions across relational and NoSQL systems, enforce engineering patterns and security standards, and optimize reliability and performance. Collaborate with Agile teams, product managers, engineers, analysts, and data scientists while mentoring peers and communicating technical concepts to stakeholders.

Analyze large-scale data, build and validate models, improve processes and reporting, evaluate products and marketing initiatives, and consult on data systems. The role requires programming, strategic analysis, collaboration across concurrent projects, and leadership in a hybrid environment.

Design, build, deploy, and support scalable cloud data platforms, pipelines, and applications for risk management. Lead technical direction across data engineering, analytics, and machine learning teams; establish reusable engineering patterns; implement security and privacy controls; and collaborate with product managers and software engineers. The role includes mentoring, stakeholder communication, distributed data processing, data modeling, warehousing, streaming, and both relational and NoSQL database solutions.

Design, build, and support scalable cloud data platforms, pipelines, and applications. Develop distributed data solutions using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Establish reusable engineering patterns, data security controls, and operational standards. Collaborate with product, engineering, analytics, and data science teams while mentoring others and communicating technical outcomes to stakeholders. Support resilient, high-performance data workloads and contribute to Agile delivery.

Design, build, and operate scalable cloud data pipelines, platforms, and applications. The role involves distributed data processing, data modeling, relational and NoSQL databases, data warehousing, security controls, observability, and real-time pipelines. The engineer collaborates with Agile teams, product managers, analysts, and software engineers; establishes reusable engineering patterns; communicates technical concepts; mentors peers; and independently delivers resilient data solutions.

Leads large-scale data engineering initiatives for Risk Tech, designing and delivering scalable cloud data platforms, pipelines, and applications. Responsibilities include architecture, data modeling, distributed processing, cloud warehousing, AI-enabled risk solutions, platform evaluation, operational resilience, and technical mentoring. The role collaborates with product managers, software engineers, analysts, and data scientists while independently driving architectural decisions and communicating technical outcomes to stakeholders.

As Senior Manager of Data Analysis, you will validate analytical tools, manage validation projects, assess quality and risks, and mentor junior staff.

Designs, builds, and operates scalable cloud data platforms, pipelines, and applications using Python, SQL, Spark, AWS, Databricks, Snowflake, and distributed data technologies. The role includes data modeling, real-time processing, data security, observability, architecture standards, stakeholder communication, mentoring, and collaboration with product, engineering, analytics, and machine learning teams.

Leads data analysis and AI-readiness initiatives for the personal loans business, including data governance, quality, automation, reporting, and analytics. Manages complex data analysis projects, improves processes and customer experiences, evaluates products and marketing initiatives, and collaborates across business units. Mentors junior analysts and contributes to data system design, business intelligence, and strategic testing.

Leads data analytics and AI-readiness initiatives for the personal loans business. Responsibilities include improving data governance and quality, automating monitoring controls, building data abstraction layers, analyzing large databases, evaluating products and processes, enhancing business intelligence, and mentoring junior analysts. The role involves cross-functional collaboration, strategic testing, reporting improvements, and consulting on data systems while managing concurrent projects.