Top Hybrid 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.

Lead data engineering initiatives for Wells Fargo’s counterparty credit risk technology team. Design, code, test, debug, document, and deploy scalable data solutions and pipelines using Python, SQL, Power BI, and related technologies. Collaborate with risk and capital markets stakeholders, resolve technical challenges, support reporting and visualization, lead projects, and mentor less experienced staff. The role requires onsite work in Charlotte or Iselin under a hybrid schedule.

Drives measurement, attribution, data analytics, and business intelligence initiatives. Integrates large-scale data from multiple platforms, performs exploratory analysis and hypothesis testing, develops predictive models, evaluates advertising campaigns, and communicates insights to executives. Ensures data integrity, governance, privacy, and security while collaborating with business leaders and data partners.

Leads customer insights and measurement initiatives by translating Voice of Customer, behavioral, operational, and business data into actionable recommendations. Defines cross-channel success metrics, governs measurement standards and instrumentation, develops automated dashboards and AI-powered insights, and drives closed-loop feedback processes. Partners with product, technology, operations, and business teams to influence priorities, improve digital experiences, and measure business impact.

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

Designs and maintains scalable data pipelines, microservices, cloud data platforms, and real-time or batch processing systems. The role uses Python, Java, AWS services, SQL, streaming technologies, automated testing, data quality controls, monitoring, and CI/CD. Responsibilities include solution architecture, data integration, stakeholder collaboration, performance tuning, production support, and ensuring reliability across distributed data ecosystems supporting construction autonomy initiatives.

Designs and maintains data visualization, reporting, and business intelligence platforms. Builds Python frameworks, dashboards, reporting applications, and analytics solutions for traders, quants, and developers. Optimizes data access and query performance, supports Looker, BigQuery, Plotly Dash, and Jupyter Notebooks, translates stakeholder requirements into technical solutions, and leads migrations across tools, libraries, and data sources.

Leads data architecture, data warehouse design, ETL development, and scalable analytics solutions using cloud and modern data technologies. Develops Python, SQL, and JavaScript code; optimizes distributed systems and CI/CD pipelines; troubleshoots production systems; evaluates emerging technologies and AI tooling; collaborates with technical and business stakeholders; and mentors junior engineers.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Leads credit card acquisition analytics for U.S. consumer and small business portfolios. Manages data scientists and analysts, develops predictive models, evaluates marketing campaigns, shapes offer and targeting strategies, and translates customer and channel insights into measurable business outcomes. Partners with product and marketing leaders, communicates findings to senior stakeholders, and promotes experimentation, model governance, scalable reporting, and continuous improvement.