Top Data Engineer Jobs in Milwaukee, WI

The Data Integration Specialist will work with clients to onboard their data to Enterra solutions, validate data processes, and communicate requirements. Responsibilities include mapping data, addressing gaps, conducting initial data wrangling, and testing solutions. The role emphasizes collaboration with data engineers and understanding client data needs.

The Staff Machine Learning Engineer will develop and fine-tune machine learning models, apply statistical techniques to analyze unstructured data, utilize pre-trained language models, optimize models for production, monitor performance, and work with teams to enhance product features and solutions.

As a Senior Consultant in Data & Analytics, you will lead clients in their analytics journey, develop strategies for data preparation, create predictive models, and provide insights through visual analytics and reporting. You will also conduct interviews for gap analysis and design data flows.

The Data Engineer Consultant at DAS42 is responsible for developing data integrations, implementing data warehouses and ETL pipelines, and optimizing clients' data environments. They work collaboratively on projects, document client data environments, and support the pre-sales process while utilizing technologies like Python and SQL alongside data visualization and cloud platforms.

As an Ad Hoc Data Processing/Data Entry Specialist, responsible for accurately entering and processing data according to company's standards and procedures. Requires high attention to detail, efficiency, and handling confidential information.

The role involves architecting, building, and maintaining reliable data pipelines, developing data applications in Python and SQL, ensuring data quality, and optimizing software engineering techniques while collaborating with IT and business teams.

As an MLOps Specialist, you will design and implement data systems and architectures to enhance data science processes. Collaborate with data scientists to improve modeling pipelines, build infrastructure, and handle data transformation. This role involves deploying models in production environments, utilizing cloud services like AWS, and supporting a team-oriented culture.