Top Data & Analytics Jobs

Build and architect scalable cloud data platforms, pipelines, and applications for Capital One’s Risk Tech organization. Responsibilities include distributed data engineering, data modeling, warehousing, streaming, security controls, and full-stack solution delivery using Python, Spark, Databricks, Snowflake, and databases. The role influences developers, analysts, and data scientists; collaborates with product and engineering teams; establishes reusable design patterns; communicates technical outcomes; and mentors data professionals.

Design, build, and operate scalable cloud data platforms and pipelines using Python, Spark, SQL, Databricks, Snowflake, and relational or NoSQL databases. Develop distributed and streaming workloads, enforce data engineering design patterns and security standards, and deliver resilient end-to-end data solutions. Collaborate with product managers, software engineers, analysts, and data scientists while mentoring team members and communicating technical concepts to stakeholders.

Leads enterprise data engineering strategy and architecture for pipelines, external data sharing, and scalable data platforms. Designs and codes critical data solutions while driving adoption of modern technologies, governance, resiliency, operational excellence, and unified data architecture. Advises stakeholders, mentors engineers, recruits talent, evaluates emerging data and AI technologies, and develops platform roadmaps. The role requires hands-on expertise across AWS, lakehouse architecture, streaming, distributed computing, data warehousing, and multiple programming languages.

Leads Enterprise Supplier Management analytics strategy, data product development, analytical tool validation, and data ecosystem improvements. Partners with senior leaders, Product, Technology, Risk, and Operations teams to evaluate business models, manage strategic priorities, assess analytical tool risk, and develop insights. Oversees and mentors a team of at least four Data Analysts while communicating findings through validation reports and presentations.

Manages data risk for Capital One’s Risk Management organization by ensuring compliance with enterprise data standards, developing governance strategies and processes, monitoring data management activities, identifying remediation needs, and reporting gaps to leadership. The role provides guidance, influences enterprise policies, collaborates with stakeholders, supports change management, and addresses risks involving complex data systems and usages.

Design, build, and operate scalable cloud data platforms, pipelines, and applications. Collaborate with data scientists, analysts, product managers, and software engineers while applying distributed data, lakehouse, streaming, database, and security technologies. Establish reusable engineering patterns, ensure performance and resilience, communicate technical outcomes, mentor team members, and deliver secure data solutions with minimal supervision.

Designs, builds, and supports scalable cloud data platforms, pipelines, and applications. Responsibilities include data modeling, distributed processing, lakehouse architecture, data warehousing, security controls, observability, and real-time data solutions. The role collaborates with product and engineering teams, influences technical standards, communicates data outcomes, and mentors data professionals while delivering resilient solutions using technologies such as Python, Spark, Databricks, and Snowflake.

Manage the development, implementation, governance, and adoption of enterprise ontologies and optimized data models. Partner with Finance, Technology, Product, Machine Learning, and enterprise teams to support ERP replacement, semantic technology integration, data standardization, and data harmonization. Own the ontology roadmap, establish standards using W3C technologies, communicate strategic vision, manage and mentor teams, and advocate for semantic technologies across the organization.

Designs, builds, and operates scalable cloud data platforms, pipelines, and applications. The role uses Python, Spark, SQL, Databricks, Snowflake, relational and NoSQL databases, and public cloud technologies. Responsibilities include data modeling, distributed data processing, security controls, architecture standards, observability, stakeholder communication, mentoring, and delivering resilient data solutions in collaboration with product, engineering, analytics, and Agile teams.

Lead the architecture and evolution of enterprise developer telemetry and real-time data platforms. Build scalable streaming pipelines, AI inference capabilities, data lake solutions, observability frameworks, and privacy controls. Correlate AI engineering metrics with business outcomes while mentoring engineers, shaping technical strategy, evaluating build-versus-buy decisions, and contributing directly through prototypes, code patterns, and reusable data products.