Top Hybrid Data & Analytics Jobs

Supports enterprise data governance and management initiatives through data analysis, lineage and cataloging, data quality improvements, policy and procedure development, SQL analysis, requirements elicitation, and stakeholder facilitation. The role collaborates with business and technical teams to implement sustainable governance processes and improve data-related workflows. This is a long-term hybrid contract requiring two onsite days weekly in Richmond, Virginia.

Supports enterprise data governance, data management, and process improvement initiatives. Responsibilities include analyzing data and business processes, improving data quality, maintaining data lineage and catalogs, creating policies and procedures, writing SQL queries, gathering requirements, facilitating stakeholders, and collaborating with technical and business teams on governance processes.

Own the design and operation of a Snowflake data platform, including Fivetran and dbt pipelines, medallion architecture, dimensional models, semantic layers, data quality, governance, and performance optimization. Migrate Power BI models from SQL Server, develop validated queries, expose governed data to AI tools and agents, and partner with business and technical teams to define reliable metrics and data models.

Build and manage enterprise datasets, reports, dashboards, analytical tools, and automated data pipelines. Combine data from multiple systems, write SQL, conduct ad hoc analyses, and partner with technology and data engineering teams to operationalize solutions. Collaborate with stakeholders across product data, merchandising, marketing, and finance, communicate findings to technical and executive audiences, and help establish analytics tools, processes, and methodologies.

Supports data engineering through code debugging, troubleshooting, solution development, peer code reviews, and system performance improvements. The intern collaborates with technical teams, reviews documentation, learns emerging technologies, and communicates solutions to team members and business leaders. The role requires current enrollment in a relevant bachelor's or higher degree program, a minimum 3.0 GPA, and programming or version-control experience. The internship is hybrid and lasts 11 weeks.

Supports customer experience and quality initiatives by designing surveys, managing Voice of the Customer processes, analyzing feedback, tracking satisfaction metrics, conducting root-cause analysis, and creating dashboards and executive scorecards. The intern presents actionable recommendations, supports continuous improvement and corrective actions, and documents processes while collaborating with quality, support, engineering, lifecycle services, and business teams.

Own product analytics for Heartflow’s platform by measuring adoption, retention, utilization, and feature impact. Design experiments and quasi-experimental analyses, establish product metrics and event taxonomies, build dashboards, and partner with Engineering on instrumentation. Translate quantitative and qualitative customer insights into product and commercial recommendations. Champion AI-enabled analytics, ensure data quality and compliance in a regulated medical-device environment, present findings to leadership, and mentor analysts.

Analyzes complex automotive data, standardizes datasets and KPI definitions, partners with engineering and governance teams, and develops scalable self-service dashboards. The role translates ambiguous business needs into data requirements, automates digital analytics programs, investigates trends and attributes, and supports enterprise reporting. It requires SQL, Excel, data visualization, statistical analysis, and AI tool experience. The position is hybrid, requiring at least 10 office days monthly, with travel up to 10%.

Analyze exchange datasets across equities, FX, options, and futures; develop liquidity and order-book metrics; and create commercial, client-ready data products. Apply statistical and machine learning methods to identify patterns, anomalies, and predictive signals. Partner with engineering, sales, marketing, internal teams, and clients on data ingestion, normalization, cloud distribution, product specifications, competitive analysis, and market-data commercialization.

Lead the architecture and implementation of scalable GCP and Databricks data lakehouse platforms. Design batch and real-time pipelines, data models, governance, cataloging, security, and performance strategies. Act as a technical lead and trusted client advisor while mentoring engineers, guiding architecture decisions, conducting proofs of concept, and supporting hands-on troubleshooting and delivery.

Collects, cleans, validates, and analyzes data from multiple sources. Develops dashboards, reports, and visualizations using SQL, Excel, Power BI, or Tableau. Identifies trends, monitors data quality, supports KPI tracking, and delivers actionable insights for business decisions. Collaborates with stakeholders, documents analytical processes, prepares regular and ad hoc reports, and recommends process improvements based on data.