Data Warehouse Engineer
About The Position
Mutual of Omaha Mortgage is seeking a highly skilled Data Warehouse Engineer to join our data engineering team. The candidate will design, develop, and maintain enterprise data solutions within Microsoft Fabric, leveraging PySpark and Python for data processing and DAG-based orchestration for workflow automation. This role oversees the evaluation, management, and optimization of data resources to ensure integrity, reliability, and performance across the organization. The successful candidate will build and maintain Fabric-based data pipelines and storage solutions, integrating multiple data sources while ensuring consistent governance, quality, and compliance. They will collaborate with engineering, analytics, and business teams to deliver scalable, well-structured data assets that support analytics and strategic decision-making. This position requires a hands-on engineer with strong technical expertise, attention to detail, and the ability to establish and enforce data standards while working independently on diverse, high-impact projects.
Requirements
- 3+ years of experience in data engineering, data warehousing, or data integration.
- Proven experience with Microsoft Fabric, including Lakehouses, Data Pipelines, Warehouses, and OneLake.
- Proficiency in Python, PySpark, and SQL for large-scale data transformations.
- Experience with Azure Data Services (e.g., Data Factory, Synapse, Databricks, or similar).
- Strong understanding of data ingestion and manipulation using APIs and modern data tools.
- Familiarity with workflow orchestration and DAG-based automation frameworks.
- Working knowledge of data modeling (star and snowflake schemas), data governance, and security best practices.
- Experience with version control systems (Git) and CI/CD processes for data deployment.
Responsibilities
- Design, build, and maintain data warehouse solutions within Microsoft Fabric, including Lakehouses, Warehouses, Data Pipelines, and OneLake assets.
- Develop and optimize ETL/ELT processes using Python and PySpark, integrating data from multiple structured and unstructured sources.
- Create and manage data ingestion pipelines using varied input types and formats (e.g., APIs, JSON, REST/SOAP, CSV, XML).
- Implement and automate data workflows through DAG-based orchestration (e.g., Airflow, Data Factory, Fabric Pipelines).
- Ensure data quality, consistency, and governance across all Fabric environments.
- Collaborate with data analysts, business users, and IT to deliver performant, scalable datasets for reporting and analytics.
- Monitor and optimize data processing performance, storage utilization, and compute efficiency in Azure and Fabric.
- Establish and maintain standards, documentation, and best practices for data architecture and operations.
- Partner with cross-functional teams and vendors to design scalable data integration patterns and maintain system reliability.
Benefits
- Vacation — Vacation hours accrue on a per pay period basis. Balance maximums are based on years of service.
- Paid Sick Time — 40 hours of paid sick time after 90 days of employment. State sick time requirements will be added as needed.
- 9 Paid Holidays + 1 Cultural Celebration Day (Floating Holiday)
- Multiple PPO Medical Plans, as well as HDHP eligible plan.
- Dental Coverage
- Vision Coverage
- Company Paid Life Insurance
- 401K with a generous employer match
- Additional Benefits including – Optional Life, FSA, Pet Insurance etc.
- Free Legal Services
- Employee Loan Program
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
501-1,000 employees
