Top Data & Analytics Jobs

Design, develop, test, implement, and support cloud-based data engineering solutions. Lead developers working with machine learning, distributed microservices, and full-stack systems. Use Java, Scala, Python, databases, data warehouses, streaming technologies, and public clouds. Collaborate with product managers and Agile teams, conduct code reviews and unit testing, optimize performance, mentor engineers, and stay current with emerging technologies.

Build and architect scalable cloud data platforms, pipelines, and applications using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Collaborate with engineering, product, analytics, and data science teams; implement secure and resilient data solutions; enforce reusable engineering patterns; communicate technical outcomes; mentor colleagues; and support distributed, real-time, and cloud-based workloads.

Design, build, and operate scalable cloud data pipelines, platforms, and applications using distributed data technologies. Lead transformative data initiatives, make architectural decisions, evaluate platforms such as Snowflake and Databricks, and ensure reliability and maintainability. Collaborate with product managers, engineers, analysts, and data scientists while mentoring peers and communicating technical outcomes to stakeholders. Apply data modeling, relational and NoSQL databases, machine learning-enabled solutions, and modern cloud architectures to support risk management products.

Analyze complex data, develop self-service data solutions, build business intelligence tools and dashboards, deliver strategic insights, and manage data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, visualization, Snowflake development, and collaboration with business and technology teams.

Analyze complex data to support business strategy, build self-service data solutions, develop dashboards and metrics, and manage data quality, metadata, lineage, security, and governance. The role requires collaboration with business and technology teams, use of Python, R, Spark, SQL, and AWS, and delivery of data-driven insights within financial services.

Leads data analysis and analytics for Capital One’s card account data products. Responsibilities include mining large databases, validating data models, improving processes and reporting, evaluating products and marketing initiatives, consulting on data systems, and collaborating across business units. The role also manages and mentors junior analysts, supports strategic product decisions, and contributes to business intelligence and project delivery.

Leads enterprise data analysis and analytical tool validation initiatives for card data products. Responsibilities include developing validation frameworks, planning validation projects, assessing methodology quality and risk, researching emerging analytical tools, prototyping best practices, preparing reports and presentations, and coaching junior staff. The role requires collaboration with data product and technology partners, independent problem solving, and management of concurrent projects.

Build and lead large-scale cloud data engineering initiatives, including cross-cloud migrations, lakehouse architecture, scalable data pipelines, data modeling, and real-time data solutions. Use Python, Spark, Databricks, Snowflake, SQL, and relational and NoSQL databases. Independently make architectural decisions, evaluate platform choices, mentor engineers, collaborate with product and software teams, and deliver reliable data platforms powering personalized travel experiences.

Analyze customer complaint and resolution data, translate business needs into product features, identify opportunities for AI and Generative AI, interpret analytical outputs, and communicate actionable recommendations to stakeholders. The role partners with technology, product, and business teams to improve workflows, decision-making, customer experience, and adoption of the Customer Navigator platform.

Build and architect scalable cloud data platforms, pipelines, and applications using Python, Spark, Databricks, SQL, and relational and NoSQL databases. Lead multi-cloud data migration into a centralized data lake, enforce engineering standards, implement security controls, support real-time data workloads, and collaborate with product, engineering, analytics, and data science teams. The role also includes mentoring, stakeholder communication, and delivering data solutions that support personalized travel products.