Data Engineer Manager Jobs in Milwaukee, WI (NOW HIRING)

Summary:

We're building great things at MGIC, and we are excited to be offering this position. This is an opportunityhelpuscreate the next generation data platform. Becoming Data-driven is at the core of our transformation - join us and help us build the future!

We arelooking for aSeniorData Engineerwhoispassionate aboutbuilding trusted, scalabledataproductswithmodern cloudtechnologies. As part of theData & Analytics team, you will design and deliver a Snowflake-centered data platform, automate source-to-warehouse ingestion with Fivetran, develop analytics-ready transformations withdbt, and orchestrate production workflows with Astronomer and Apache Airflow.

Responsibilities:

• Define and evolve data integration frameworks, engineering standards, reusable patterns, and governance practices for a modern cloud data platform.

• Design scalable Snowflake data architectures, including databases, schemas, tables, views, virtual warehouses, role-based access, and approaches for performance and cost optimization.

• Build and operate reliable batch and incremental ingestion pipelines using Fivetran connectors, including source configuration, schema-change handling, sync monitoring, troubleshooting, and custom connector patterns when needed.

• Develop modular, maintainabledbtmodels in Snowflake; implement source definitions, tests, documentation, lineage, incremental strategies, and reusable macros.

• Author, schedule, deploy, and monitor data workflows with Apache Airflow on Astronomer, applying effective dependency management, retry, alerting, backfill, and failure-recovery practices.

• Implement observability and data-quality controls across ingestion, orchestration, and transformation layers so production data is accurate, timely, and available to stakeholders.

• Partner with business, analytics, architecture, security, and engineering teams to translate requirements into durable data products and a long-term platform roadmap.

• Deliver changes through Git-based development, automated testing, code review, and CI/CD practices acrossdbtand Airflow projects.

• Troubleshoot data and pipeline issues across source systems, Fivetran, Astronomer,dbt, Snowflake, and downstream consumption layers.

• Evaluate Cortex Code capabilities and lead the development of a practical adoption plan for incorporating AI-assisted engineering into solution delivery processes, including prioritized use cases, governance and security guardrails, developer workflows, enablement, success measures, and a phased rollout.

• Lead design and code reviews, share engineering best practices, and mentor junior data engineers.

Required skills:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or relevant experience.

• 5 or more years of data engineering experience, including cloud data warehousing, dimensional data modeling, ETL/ELT, analytics enablement, and production pipeline support.

• Hands-on Snowflake experience, including advanced SQL, data loading and transformation, virtual warehouse sizing, query optimization, access controls, and cost-conscious platform operation.

• Experience building production-gradedbtprojects with modular models, tests, documentation, source freshness, incremental models, macros, packages, and CI/CD.

• Experience developing and operating Apache Airflow DAGs; familiarity with Astronomer or another managed Airflow platform, including deployment, monitoring, alerting, and troubleshooting.

• Experience implementing and supporting managed ELT with Fivetran, including connector setup, incremental synchronization, schema evolution, monitoring, and issue resolution.

• Strong Python and SQL skills; experience with APIs, data formats, shell scripting, and Git-based development workflows.

• Experience with AWS services such as S3, Lambda, IAM, and related cloud data services, plus Agile delivery and end-to-end automation practices.

• Knowledge of Cortex Code and AI-assisted software development practices, ordemonstratedwillingness and ability to build a responsible adoption plan that integrates the technology into solution delivery processes while maintaining security, governance, code-review, testing, and change-management standards.

• Strong communication, problem-solving, and collaboration skills, with the ability to influence technical decisions and mentor other engineers.