Top Remote Data & Analytics Jobs in Milwaukee, WI

Design, build, and own business-critical data infrastructure, including AWS Glue and Spark pipelines, cloud warehouse or lakehouse systems, orchestration, and Tableau BI platforms. Define event-driven contracts, data models, schemas, observability, and batch or streaming architectures across multi-tenant, multi-region environments. Collaborate across producer and consumer teams while owning production data infrastructure and outcomes end to end.

Manages the daily operations and maturation of a federated enterprise data governance program. Leads governance councils and stewardship groups, defines roles, develops policies and guidance, drives stakeholder adoption and training, and advances data quality, metadata, lineage, and issue resolution practices. Partners with legal, privacy, security, compliance, business, technical, and external stakeholders while maintaining governance documentation, monitoring program performance, and coordinating approvals and improvements.

Lead a BI engineering team, overseeing dashboards, data models, SQL/dbt transformations, ETL pipelines, Airflow DAGs, data warehouses, CI/CD, governance, and quality standards. Partner with stakeholders to define reporting requirements, conduct advanced analyses, manage Agile projects, and develop data strategy. Mentor team members and support production deployments. This fully remote role requires travel to Denver for five business days each quarter.

The Database Administrator III role requires U.S. citizenship and completion of all work within the continental United States, Alaska, or Hawaii. The provided description does not specify database administration responsibilities, tools, or technical qualifications. Compensation is $120,000 to $150,000 annually.

The BI Engineer administers enterprise BI and analytics platforms, governs data consumption, and develops dashboards, reports, KPIs, and self-service analytics. The role translates business requirements into scalable, validated solutions; manages access controls, metadata, data quality, continuity planning, platform costs, and process improvements. It also provides stakeholder consultation, resolves complex technical issues, mentors teammates, and supports enterprise data transformation using Power BI, Tableau, Azure, SQL, and multiple database technologies.

Leads the architecture, design, and implementation of Azure-based analytics and data engineering solutions. Develops and optimizes data pipelines, ETL/ELT processes, query layers, Delta Lake solutions, and integrations across Databricks, Azure Data Lake, Synapse, Data Factory, and Power BI. Partners with stakeholders, oversees end-to-end delivery, ensures security and governance, documents data flows, and mentors data engineers while promoting scalable, high-quality solutions.

Advances the firm’s clinical analytics platform, translating pharmacy and utilization-management expertise into scalable analytical frameworks. Partners with financial, analytics, clinical, and payer teams to standardize insight generation, validation, and communication. Develops pharmacist training, mentorship, educational materials, and enterprise clinical guidance while supporting specialty-drug, medical-pharmacy integration, and outcomes-focused strategy.

Serve as the technical authority for the Enterprise Data Platform, defining enterprise data architecture, canonical data and semantic models, externalization and API principles, and AI/knowledge-graph ready designs. Lead solution architecture, govern semantic layers and Collibra integration, chair architecture reviews, shape technology roadmap, and partner with platform and trust teams to ensure consistent, governed data products across delivery teams.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

The Staff Product Analytics Engineer will enhance product data usage across teams by owning data infrastructure, creating tools for self-service data, and ensuring data-driven decisions. Responsibilities include collaborating with various teams to improve data insights and maintain data pipelines.