Top Data Engineer Jobs in Milwaukee, WI

Lead design and delivery of scalable production data pipelines and data products (Spark/Python/SQL) on Databricks; integrate diverse federal health systems, define reusable ingestion patterns, ensure data quality/governance, mentor engineers, and troubleshoot/optimize production workflows.

Design, build, and operate scalable batch and streaming data pipelines and a lakehouse on AWS. Implement ETL/ELT, CDC, metadata/cataloging, lineage, governance, data quality, IaC, and CI/CD for reliable, observable, and secure data platforms to support analytics and ML.

Build and maintain scalable ETL/data pipelines and internal frameworks to support ML and product teams. Drive architecture, observability, data quality, and engineering best practices across AI/ML workflows and prompt-engineering pipelines.

Lead design, build, and operate scalable Databricks/Delta Lake data pipelines and Kimball dimensional models using dbt. Manage governance with Unity Catalog, optimize performance and cost, operationalize ML with MLflow, and coordinate/quality-check offshore vendor engineering. Mentor engineers, uphold standards, and deliver trusted data products that power analytics, reporting, and MLOps workflows.

Design, build, and maintain scalable data pipelines, data models, ETL/ELT, and BI solutions. Collaborate with data scientists and stakeholders to improve data quality, accessibility, and PHI security. Develop and document workflows, optimize processing/storage, support data warehouse and visualization, and adopt AI tools to drive data-informed outcomes.

The Senior Data Engineer will construct and optimize data pipelines, work with cross-functional teams, ensure data quality and governance, and mentor junior engineers while leading advanced analytics initiatives.

Design, build, and operate scalable data transformation pipelines and dimensional models using dbt, SQL, and AWS. Implement infrastructure-as-code (AWS CDK), CI/CD, and query performance optimizations while ensuring data quality, governance, and collaboration with cross-functional and offshore teams.

Lead Data Engineer builds and maintains scalable data pipelines and lakehouse/warehouse platforms (Databricks) to support analytics, BI, reporting, and AI. Responsibilities include data modeling, ETL/ELT, medallion architecture, orchestration and monitoring (Airflow/Cron), performance tuning, CDC/incremental loads, data quality, and leading/mentoring a team while collaborating with stakeholders and maintaining documentation.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Design and implement data federation and lakehouse architectures, build scalable ETL/ELT pipelines with Python and Spark, optimize performance across federated queries, manage Delta/Iceberg/Hudi tables, and enforce governance, security, and access controls for analytics and AI teams.

Design, build, test, and maintain high-performance Python data applications and backend services. Lead technical design, review code, mentor junior engineers, integrate with databases and cloud services, optimize performance, and ensure security, scalability, and reliability.

Design, develop, maintain, and optimize enterprise Tableau dashboards and BI solutions. Integrate and cleanse data from Oracle/Sybase/Big Data, tune SQL, automate Tableau extracts, manage Tableau Server on Linux, support testing, UAT, deployments, and troubleshoot data integrity and performance issues.

Design, build, and operate a Snowflake-centered cloud data platform: ingest with Fivetran, transform with dbt, orchestrate with Airflow/Astronomer, ensure observability and data quality, deliver CI/CD workflows, troubleshoot pipelines, guide Cortex Code adoption, and mentor junior engineers while partnering with cross-functional teams.

Design, build, and operate scalable, production-grade ingestion pipelines (Fivetran, APIs, files) to bring Workday and other HR/payroll data into the data platform. Ensure data reliability, monitoring, schema management, and handoffs to downstream transformation teams while optimizing connectors, syncs, and costs.

Own the 2-3 year architecture and reliability of high-volume catalog, pricing, and inventory ingestion. Lead migrations from legacy batch to modern systems, define data SLAs, build observability and orchestration, mentor senior engineers, and resolve cross-team, high-severity data problems.

Design, build, and maintain scalable batch and streaming data pipelines, improve data modeling and governance, contribute to enterprise data architecture, and collaborate with cross-functional teams to ensure reliable, high-quality data for analytics and operational use.

Design, build, and maintain data pipelines and analytics-ready datasets using SQL and cloud data platforms. Perform data profiling, validation, and source-to-target mapping. Support BI enablement, document transformations, and collaborate with stakeholders while following data governance and security practices.

Design, build, and optimize scalable end-to-end data pipelines and Snowflake data warehouses. Develop BI solutions (Power BI/Tableau/Cognos), enforce data quality/governance, integrate investment data vendors, collaborate with stakeholders, mentor junior engineers, and follow SDLC/DevOps best practices.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.

Design, build, and maintain an internal data platform enabling secure, governed access for engineering and analytics. Partner with architects, implement data pipelines and automations, enforce security and compliance, support platform services, recommend architecture improvements, mentor teams, and drive adoption of scalable, self-service data capabilities.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

Lead a team of data engineers to design, build, and maintain scalable data pipelines, a Data Vault, data warehouses and marts. Own backlog, sprint planning, mentoring, stakeholder collaboration, data validation/monitoring, and platform improvements to deliver key metrics and data infrastructure across the business.

Design, deploy, and maintain scalable data infrastructure and orchestration for analytics and ML; write optimized SQL over large warehouses; partner with engineering and product to structure source systems; maintain CDC pipelines; scale reporting and expose analytical datasets enterprise-wide while ensuring data management, security, and compliance.