Top Data & Analytics Jobs

Extracts, transforms, and loads data from diverse sources; develops Power BI dashboards and reports; maintains data governance, quality, lineage, metadata, security, and retention practices; documents ETL processes, APIs, and reporting solutions; trains stakeholders; troubleshoots data pipelines; and identifies opportunities for automation and process improvement.

Own Pursuit’s data infrastructure, semantic layer, data dictionary, reporting, dashboards, and AI-enabled capabilities. Improve data quality and self-service access while designing structures with cross-functional teams. Establish data governance for reliable human and AI-agent use, evaluate AI workflows, integrate SaaS systems, and administer permissions and workflows. The role requires hands-on technical work, cross-functional project management, stakeholder communication, and high ownership of scalable data systems.

Creates, analyzes, edits, and maintains GIS data supporting fiber and HFC network planning, design, construction, and regulatory map updates. Uses ArcGIS and ArcFM to manage geodatabases, spatial datasets, parcel data, route assets, and network schematics. Conducts map research, interprets technical records, supports GIS projects, develops mapping standards, and responds to internal requests. Collaborates with legal, market expansion, engineering, construction, and design teams while ensuring geospatial data quality and alignment with GIS best practices.

Own the end-to-end data architecture for multi-tenant enterprise SaaS and analytics products. Lead Azure SQL, Databricks, data lake, warehouse, BI, lifecycle management, ERP/SAP integration, observability, schema evolution, and data SLO initiatives. Manage DBA and database engineering standards, reliability, performance, HA/DR, and incident response while mentoring data engineers and partnering with product, projects, and BI teams.

Owns end-to-end customer data conversions into a dental practice management platform. Responsibilities include extracting, profiling, mapping, cleaning, transforming, loading, and validating legacy data using SQL, Excel, and conversion tools. The role manages timelines, customer approvals, quality assurance, troubleshooting, documentation, and production go-lives while collaborating with implementation and support teams.

Manage DTC analytics, reporting, dashboards, KPI measurement, A/B testing analysis, and ecommerce performance tracking. Query and analyze data using SQL and BI tools, automate reporting, identify business drivers, and translate findings into actionable recommendations. Partner with Product, Engagement, CX, Distribution, Finance, and senior stakeholders to improve decision-making, challenge assumptions, and shape analytics strategy. Apply AI tools to streamline analysis and reporting processes.

Interns will work with Data Solution Engineers to solve business problems and build data assets for actuarial and product management teams. They will receive training in Snowflake, SQL, Azure Data Factory, Azure Databricks, SAS, SQL Server, Python, and Power BI; collaborate with mentors; complete project tasks; and participate in community service. The role is fully in-office in West Bend or Madison, Wisconsin.

Manage DTC analytics by building KPI reporting, dashboards, A/B testing analyses, and automated tools across the customer journey. Translate data into actionable recommendations, identify business and customer drivers, improve ecommerce performance measurement, and serve as a trusted thought partner to DTC, Product, Engagement, Distribution, Finance, and senior stakeholders. The role requires strong SQL skills, BI platform expertise, business judgment, storytelling, and effective communication.

Analyze product and underwriting data to identify trends, develop metrics, conduct ad hoc queries, and support operational dashboards. Translate quantitative findings into actionable recommendations for leadership through data storytelling. The role requires collaboration with business teams, strong analytical problem-solving, and proficiency with Excel, PowerPoint, Python, or SQL.

Build and maintain data pipelines using ETL/ELT, Databricks, Python, Spark, and Airflow. Manage data transformations, databases, schemas, and data quality controls. Support reporting, analytics, and machine learning integrations while deploying solutions in AWS. Automate workflows, troubleshoot data issues, document processes, and collaborate with data scientists, analysts, database administrators, and business stakeholders.