Top Senior Data & Analytics Jobs in Milwaukee, WI

The Senior Korean Linguist manages translation and copy-editing tasks, coordinates with freelancers, and ensures high-quality Korean-language deliverables while improving workflows and supporting quality efforts.

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and influence product analytics standards and long-term strategy.

As a Senior Data Analyst, you'll provide actionable insights by analyzing product and engineering data, partnering with leadership on metrics frameworks and decision support for product delivery.

Design, build, and operate Alpaca's scalable data platform and lakehouse infrastructure. Build low-latency streaming and CDC ingestion, batch pipelines landing in Iceberg, and tooling for BI and AI consumers. Manage IaC, Kubernetes deployments, monitoring/incident response, and partner with DevOps and analytics teams to meet growing data requirements.

Lead design and governance of a large-scale AdTech data layer: model conceptual/logical/physical schemas, profile and map data flows, define batch and real-time ingestion and integration patterns, architect cloud-native AWS solutions (including graph/vector/RAG use cases), establish governance, and produce architecture artifacts and implementation roadmaps while collaborating with engineering, product, and cloud teams.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

The Senior BI Analyst will gather requirements, develop scalable reporting solutions, and create dashboards using Power BI, ensuring data-driven decisions across the organization.

Lead design, implementation, and optimization of cloud-native data platforms (Snowflake, AWS, Azure) for managed-services clients. Translate business requirements into secure, scalable architectures, drive migrations and performance tuning, and provide hands-on technical leadership. Collaborate with cross-functional teams, mentor junior engineers, and contribute to best-practice frameworks, automation, and pre-sales efforts.

Customer-facing specialist guiding enterprise cloud data engineering and lakehouse transformations. Architect and optimize large-scale data pipelines, perform performance and load testing, support pre-sales POCs and workload sizing, lead adoption workshops, and mentor peers to drive Databricks platform adoption.

Lead process mapping, analysis, and redesign to improve efficiency and outcomes. Partner with stakeholders to gather requirements, analyze data (SQL, Excel, Power BI), define KPIs, apply Lean/Six Sigma methods, and support automation and digital transformation initiatives to drive growth, profitability, and loss reduction.