Top Data & Analytics Jobs

Build scalable data pipelines, dimensional data marts, and reusable data products for analytics, automation, and AI-powered workflows. Partner with Data Science, Product, Engineering, and Operations to support self-service analytics, data governance, quality, security, and analytics engineering standards. Develop agentic tools, promote dimensional modeling, and deliver well-tested, documented data solutions that support experimentation and the company’s banking initiatives.

Designs and evolves the organization’s data warehouse, semantic layer, transformation pipelines, data products, and reusable analytics assets. The role implements data governance, quality testing, monitoring, alerting, documentation, and scalable data models across cloud platforms. It partners with data engineering, analytics, research, and governance stakeholders to support self-service analytics and AI readiness while influencing long-term data platform strategy.

Lead actuarial analyses, evaluate statistical methods, stress-test and validate internal cyber risk models, investigate data quality, interpret findings, and communicate results to internal and external stakeholders. The role also supports research and development, underwriting and actuarial tool enhancement, documentation, and analytical assistance for team members.

Build Reducto’s data infrastructure from the ground up, owning warehouses, databases, pipelines, orchestration, transformations, data modeling, reliability, testing, freshness, and lineage. Integrate product, sales, and finance data into trusted company-wide datasets. Partner with Engineering, Finance, Operations, and GTM leaders to define business metrics and priorities. As the founding data hire, establish scalable architecture and standards while supporting analytics and business decision-making.

Designs, builds, and owns enterprise data infrastructure supporting analytics, machine learning, and AI applications. Responsibilities include developing scalable ETL/ELT pipelines, API and database integrations, data models, ingestion frameworks, lake and warehouse architectures, Power BI reporting assets, data quality monitoring, governance, lineage, and reproducibility practices. The role partners with data scientists, machine learning engineers, business teams, and IT while supporting healthcare data environments and third-party data negotiations.

Participate in the software development life cycle, including design, database and code implementation, testing, debugging, troubleshooting, documentation, and maintenance. Collaborate in Agile development meetings, write structured code, complete assigned projects, and consult with team members to achieve desired results. The role is intended for a Computer Science or related bachelor's student with strong problem-solving, critical-thinking, teamwork, and learning abilities.

Administer and support SQL Server and cloud databases for a tolling environment. Responsibilities include database monitoring, installation, upgrades, patching, migration, performance tuning, troubleshooting deadlocks and blocking, resolving application connectivity issues, supporting high availability, and managing very large databases. The role also provides help desk and application support, uses operating-system scripting, and recommends database improvements while collaborating with engineering and operations teams.

Leads operations intelligence and business solutions for Logistics & Distribution. Translates business needs into reporting, analytics, automation, and AI-enabled tools; develops Tableau and Power BI dashboards, data models, KPI frameworks, and executive insights. Identifies process improvements, evaluates AI use cases, builds Power Platform solutions, supports governance and adoption, and partners with Technology and business teams on scalable solutions, ROI analysis, and digital transformation.

Own production-grade analytics data products, including reusable dbt models, dimensional models, metrics, access controls, tests, documentation, and Lightdash guidance. Partner with stakeholders across GTM, Finance, and data teams to define requirements, reconcile conflicting source data, validate results, and publish trusted metrics. Diagnose data quality issues, collaborate with data engineering, review modeling changes, and establish shared standards. Regularly use and evaluate AI coding agents in analytics workflows.

Build and maintain business intelligence models, dashboards, reports, and compensation analyses for shelter, breeder, and sales channels. Support insurance regulatory reporting, ad hoc analytics, data quality, governance, automation, and performance tuning. Partner with data engineering, compliance, and business teams to improve enterprise data models and enable AI-driven initiatives.