Top Data & Analytics Jobs in Milwaukee, WI

Gather and document business and data requirements, translate needs into functional specs and source-to-target mappings, write SQL to profile and validate data, interpret Duck Creek policy XML and map to Insights tables, collaborate with developers/data engineers, support data quality/governance and reporting, facilitate stakeholder meetings, and assist support teams with data issue analysis.

Develop and deliver Informatica ETL solutions for data warehousing projects: extract from varied sources, design and test mappings, analyze business rules and data issues, produce design artifacts, collaborate across teams, support production, and contribute to estimates and configuration management.

Designs and architecting data solutions, manages project delivery, ensures alignment with architecture policies, and oversees data accuracy and MDM standards.

The Sr. Data Engineer will develop applications, support database performance, assist with data analytics, and implement data quality measures.

The role involves design and development using Markit EDM, analyzing code, preparing design documents, and implementing data integration projects.

Design and deliver enterprise Power BI dashboards, reports, and semantic models. Gather requirements, prototype, iterate with stakeholders, productionize solutions (testing, security, administration), mentor junior consultants, and align visualizations to business objectives and user needs.

Design, build, and maintain Power BI and Tableau dashboards; analyze large, complex datasets using SQL, Python, and statistical methods; partner with data engineering and business stakeholders to ensure data quality; translate findings into clear, actionable stories and executive-level presentations; support firmwide analytics growth and automation.

Analyze business data, build and maintain business models, provide actionable insights and reports, collaborate with cross-functional teams, monitor performance, and recommend efficiency improvements to support strategic decision-making.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Support building and maintaining ETL/ELT data pipelines and cloud data workflows. Work with senior engineers and cross-functional teams to implement, test, deploy, and document data processes. Continuously learn cloud technologies, SQL, and Python/PySpark, follow coding best practices, and contribute to process improvements in an Agile environment.

Design, build, and maintain scalable data pipelines and ETL/ELT frameworks using Python and PySpark. Develop reusable components, microservices, and cloud-based data solutions on AWS and Snowflake. Ensure code quality via reviews, CI/CD, logging, and best practices while collaborating with stakeholders to solve data problems.

Lead customer-facing data engineering and warehousing initiatives on the Databricks platform. Architect and optimize production-scale ETL/ELT pipelines, performance-test workloads, migrate legacy systems to cloud lakehouse architectures, support Solution Architects in technical sales, and provide training, demos, and community contributions.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.