Data Engineer, Home Lending Data & Insights
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Role details
Tech stack
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Job description
The Home Lending Data & Insights team delivers enterprise-scale data products and analytics solutions that power critical mortgage lending operations. We are seeking a Senior Data Engineer to design, build, and modernize data pipelines supporting a complex ecosystem of mortgage application, loan processing, imaging, and servicing platforms.
In this role, you will help transform large-scale data assets into trusted, high-quality datasets that drive business decisions across the Home Mortgage organization. You will work on both traditional enterprise ETL solutions and cloud modernization initiatives, helping migrate data platforms and workloads to Google Cloud.
This position is ideal for an engineer who enjoys solving complex data challenges, building scalable solutions, and partnering closely with product, architecture, and business teams. What You’ll Do
- Design, develop, and optimize scalable batch and near real-time data pipelines.
- Build and maintain enterprise ETL solutions using Ab Initio, Python, PySpark, SQL, and PL/SQL.
- Integrate, cleanse, transform, and standardize data from multiple mortgage and financial systems.
- Translate technical requirements and solution designs into reusable, maintainable code.
- Partner with Product Owners, Architects, and business stakeholders to deliver reliable data products.
- Support cloud migration and modernization initiatives leveraging Google Cloud Platform (Google Cloud Platform).
- Build and deploy solutions through automated CI/CD pipelines.
- Troubleshoot production issues, perform root cause analysis, and drive continuous improvements in reliability and performance.
- Implement data quality controls, monitoring, governance, and lineage best practices.
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Contribute to Agile development practices across distributed global teams., Technical Stack Data Engineering & ETL
- Ab Initio
- ETL Design & Development
- Oracle
- Teradata
- Data Warehousing
- Data Modeling
Programming
- Python
- PySpark
- SQL
- PL/SQL
- Unix Shell Scripting
Cloud & Analytics
- Google Cloud Platform (Google Cloud Platform)
- BigQuery
- Dataplex
- Cloud Migration & Modernization
Scheduling & Orchestration
- AutoSys
- Apache Airflow
- Google Cloud Composer
CI/CD & DevOps
- Jenkins
- Harness
- uDeploy
- Git
- Automated Testing & Deployment
Data Quality & Governance
- Informatica Data Quality
- Data Profiling
- Data Governance
- Metadata Management
- Data Classification & Lineage
Team & Culture
You’ll join a collaborative organization consisting of three Agile Scrum teams across the U.S. and India. The team values technical excellence, knowledge sharing, continuous improvement, and ownership. Strong onboarding, documentation, and support processes are in place to help new team members quickly become productive.
Requirements
- 4+ years of experience in Data Engineering, ETL Development, or related disciplines.
- Hands-on experience developing complex ETL solutions using Ab Initio.
- Strong SQL and PL/SQL skills with experience in Oracle, Teradata, BigQuery, or comparable enterprise databases.
- 3+ years of software development experience using Python and PySpark.
- Experience designing and supporting enterprise data warehousing solutions.
- Experience with Unix/Linux environments and shell scripting.
- Strong analytical and problem-solving skills with the ability to work across large, complex data ecosystems.
- Experience building, testing, and deploying solutions through CI/CD processes., * Experience in Financial Services, Banking, Mortgage Lending, or highly regulated environments.
- Experience modernizing legacy ETL platforms and migrating workloads to cloud-native architectures.
- Hands-on experience with Google Cloud Platform, including BigQuery, Dataplex, Cloud Composer, or related services.
- Experience with workflow orchestration tools such as AutoSys, Airflow, or Cloud Composer.
- Knowledge of data governance, metadata management, lineage, and data quality practices.
- Experience with Informatica Data Quality or similar data quality frameworks.
- Familiarity with Git-based development workflows, code reviews, automated testing, and DevOps practices.
- Experience with CI/CD platforms including Jenkins, Harness, and uDeploy.
- Understanding of near real-time and event-driven data processing architectures.
- Experience using AI-assisted development tools to improve engineering productivity and code quality., * Deep hands-on experience with ETL development and data integration.
- Experience working in large-scale enterprise environments.
- Success modernizing legacy data platforms.
- Ability to learn quickly, adapt to new technologies, and solve challenging problems.
Top Skills
- Ab Initio & Unix Shell Scripting
- Python / PySpark
- CI/CD & DevOps Automation
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