Top Data & Analytics Jobs

Design, build, and operate scalable cloud data platforms, pipelines, and applications. The role involves distributed data processing, data modeling, relational and NoSQL databases, warehousing, streaming, security, and observability. The engineer collaborates with Agile teams, architects reusable engineering patterns, communicates technical outcomes, mentors colleagues, and delivers resilient data solutions using technologies such as Python, Spark, Databricks, and Snowflake.

Design, build, deploy, and support scalable cloud data solutions, pipelines, platforms, and applications for enterprise risk management. The role uses Python, Spark, SQL, relational and NoSQL databases, Databricks, Snowflake, and cloud technologies. Responsibilities include data modeling, distributed and streaming workloads, security controls, architecture standards, observability, operational efficiency, stakeholder communication, mentoring, and collaboration with product, engineering, analytics, and machine learning teams.

Leads quantitative model risk analysis for loan loss forecasting and allowance for credit losses. Evaluates model soundness, performance under stress scenarios, regulatory alignment, and model risk. Develops alternative approaches, applies econometric, statistical, and machine learning methods, improves model frameworks, documents findings, and communicates complex results to management, regulators, and technical audiences. Collaborates with model development and risk teams while supporting continuous improvement and Agile delivery.

Leads pricing and analytics strategy, prioritizes analytical requests, translates ambiguous business questions into recommendations, and delivers executive insights. Owns business strategy, product and pricing analytics, credit risk modeling, marketing insights, and cross-functional execution. May manage analysts, oversee projects, develop business requirements, and partner with Sales, Finance, IT, Operations, and other teams to improve profitability and performance.

Design, build, and architect scalable cloud data platforms, pipelines, and applications. Lead large-scale data initiatives, make architectural decisions, evaluate technologies such as Snowflake and Databricks, enforce engineering patterns, and ensure performance and resilience. Collaborate with product, engineering, analytics, and data science teams while mentoring engineers and communicating technical outcomes to stakeholders.

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, resilient, reusable data solutions; support distributed and streaming workloads; apply data modeling and observability practices; communicate technical concepts; and mentor other data engineers.

Leads analytics and strategy for Capital One Travel by monitoring performance, analyzing booking behavior, identifying growth opportunities, and optimizing margins and volume. Partners with Product and cross-functional teams on initiatives, pricing, marketing, and credit risk analytics. May manage analysts, develop business requirements, oversee projects, and communicate recommendations to executives. Requires strong SQL, quantitative analysis, strategic judgment, leadership, and communication skills.

Performs advanced data analysis across innovation, business intelligence, and data management. Builds data solutions, self-service tools, dashboards, metrics, and visualization capabilities; analyzes complex datasets; partners with business and technology teams; and supports data quality, metadata, lineage, security, access governance, and monitoring. Requires strong scripting, data querying, BI, AWS, and data governance experience.

Validates and enhances balance sheet forecasting, stress testing, capital markets, and financial risk models. Develops quantitative and machine learning solutions, analyzes large datasets, performs model testing and benchmarking, documents findings, and communicates results to business leaders and technical stakeholders. Collaborates across teams to build cloud-based analytical solutions and improve risk management processes.

Leads enterprise analytical tool validation, assessing methodology quality, risk, technical issues, and business impact. Plans validation projects, researches emerging practices, develops solutions, communicates findings through reports and presentations, and mentors junior staff. The role requires extensive data analysis, statistical or econometric modeling, open-source data technology experience, data governance knowledge, predictive analytics expertise, and people management.