Senior Data Engineer
At MGIC , we take pride in knowing that what we do matters. As pioneers of private mortgage insurance, we help people achieve homeownership sooner - making affordable low-down-payment mortgages a reality. Our efforts have helped more than 14 million people get the keys to their own homes sooner than otherwise possible. Every position is critical to our company's success - from the analytical to the technical; from the innovative to the operational. The customer-facing roles to behind-the-scenes experts, we're all part of one team. We're an organization with a national footprint that's large enough to never lack for a new challenge, but small enough for an opportunity to make an impact and influence decisions. Come make a difference at MGIC .
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:
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Define and evolve data integration frameworks, engineering standards, reusable patterns, and governance practices for a modern cloud data platform.
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Design scalable Snowflake data architectures, including databases, schemas, tables, views, virtual warehouses, role-based access, and approaches for performance and cost optimization.
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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.
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Develop modular, maintainabledbtmodels in Snowflake; implement source definitions, tests, documentation, lineage, incremental strategies, and reusable macros.
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Author, schedule, deploy, and monitor data workflows with Apache Airflow on Astronomer, applying effective dependency management, retry, alerting, backfill, and failure-recovery practices.
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Implement observability and data-quality controls across ingestion, orchestration, and transformation layers so production data is accurate, timely, and available to stakeholders.
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Partner with business, analytics, architecture, security, and engineering teams to translate requirements into durable data products and a long-term platform roadmap.
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Deliver changes through Git-based development, automated testing, code review, and CI/CD practices acrossdbtand Airflow projects.
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Troubleshoot data and pipeline issues across source systems, Fivetran, Astronomer,dbt, Snowflake, and downstream consumption layers.
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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.
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Lead design and code reviews, share engineering best practices, and mentor junior data engineers.
Required skills:
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Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or relevant experience.
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5 or more years of data engineering experience, including cloud data warehousing, dimensional data modeling, ETL/ELT, analytics enablement, and production pipeline support.
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Hands-on Snowflake experience, including advanced SQL, data loading and transformation, virtual warehouse sizing, query optimization, access controls, and cost-conscious platform operation.
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Experience building production-gradedbtprojects with modular