Job description

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 opportunity help us create the next generation data platform. Becoming Data-driven is at the core of our transformation – join us and help us build the future! We are looking for a Senior Data Engineer who is passionate about building trusted, scalable data products with modern cloud technologies . As part of the Data & Analytics team , you will design and deliver a Snowflake-centered data platform, automate source-to-warehouse ingestion with Fivetran, develop analytics-ready transformations with dbt , 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, maintainable dbt models 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 across dbt and 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-grade dbt projects 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, or demonstrated willingness 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. Pay Range: $105,590.00 - $179,510.00 This range aligns with current market data and reflects our commitment to competitive and equitable compensation. Salary offers are based on factors such as experience, skills, education, and training. The range may vary in certain locations to reflect local market conditions. It is not typical to initiate pay at the top of the range to account for internal equity and allow for future and continued salary growth Enjoy these benefits from day one: • Competitive Salary & pay-for-performance bonus • Financial Benefits (401k with company match, profit sharing, HSA, wellness program) • On-site Fitness Center and classes (corporate office) • Paid-time off and paid company holidays • Business casual dress For additional information about MGIC and to apply, please visit our website at www.mgic.com/careers . Note to all recruitment agencies: MGIC does not accept unsolicited agency resumes. Any unsolicited resumes sent to MGIC, directly or indirectly, will be considered MGIC property. MGIC is not responsible for any agency fees associated with unsolicited resumes. A recruiting agency must have a valid, written and fully executed agency agreement to assist with a requisition.

Requirements

Must-haves

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.
Develop modular, maintainable dbt models 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 across dbt and Airflow projects.
Troubleshoot data and pipeline issues across source systems, Fivetran, Astronomer, dbt , Snowflake, and downstream consumption layers.
Lead design and code reviews, share engineering best practices, and mentor junior data engineers.
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-grade dbt projects 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.
Strong communication, problem-solving, and collaboration skills, with the ability to influence technical decisions and mentor other engineers.
$105,590.00 - $179,510.00
On-site Fitness Center and classes (corporate office)
Business casual dress
For additional information about MGIC and to apply, please visit our website at www.mgic.com/careers .

Nice-to-haves

Competitive Salary & pay-for-performance bonus

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

ci/cdaisqlpythonawsagile

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

401k

Wellness