Power Platform Developer

The Home Lending Data & Insights team supports the Home Mortgage organization by delivering enterprise data products and solutions. The team manages complex data ecosystems involving mortgage application processing, imaging platforms, loan processing systems, and other supporting mortgage applications. The selected consultant will primarily support the Core Downstream application, which receives and processes mortgage application data. This role is focused on consolidating data from multiple repositories, cleansing and transforming it, and delivering trusted data assets to business consumers. This is a hands-on Senior Data Engineer / ETL Developer role that combines traditional enterprise ETL development with cloud modernization initiatives.

1. U.S.-based team
2. India-based teams

Approximately 14 team members supporting the application Strong onboarding process and documentation in place to bring people up to speed Contractors currently work onsite five days per week Contract position with potential interest in future conversion Key Responsibilities: Build and maintain scalable batch and near real-time data pipelines Develop ETL solutions using Ab Initio, Python, PySpark, SQL and

PL/SQL

Review technical designs and convert solution blueprints into reusable code Integrate, cleanse, normalize, and transform data from multiple mortgage-related systems Partner with Product Owners, Architects, Engineers, and business stakeholders Support migration and modernization initiatives from legacy platforms to Google Cloud Build, schedule, orchestrate, and deploy solutions through enterprise CI/CD pipelines Support monitoring, operational excellence, root cause analysis, and production reliability Required Qualifications: 4 plus years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 4 plus years PL/SQL and SQL skills with proven experience in Oracle, Teradata, Python and/or BigQuery: complex query development, tuning, and debugging. 4 plus years Ab Initio skills with proven experience to build complex graphs, Psets, performance tuning. 3 plus years programming skills in Python; hands-on PySpark for distributed data processing 3 plus years of ETL/ETL design, data warehousing concepts, and data modeling best practices Desired Qualifications: Financial Services or Mortgage industry experience Production operations experience: monitoring, SLAs, incident response, root cause analysis, and performance optimization. Experience working in hybrid environments (on-prem + cloud) and supporting data migration/modernization initiatives. Experience with scheduling/orchestration in Autosys and Airflow-based orchestration (Cloud Composer direction). Experience with Git-based workflows, code reviews, and automated testing practices for data pipelines. Experience with Harness, Jenkins and uDeploy based CICD environments. Practical experience using AI-assisted coding tools in daily development to improve productivity without compromising quality or security. Ab Initio development/maintenance experience and/or hands-on migration of Ab Initio graphs to modern Spark/SQL patterns. Experience with Dataplex and broader data governance concepts (metadata, classification, stewardship, lineage practices). Experience with Informatica Data Quality implementation patterns (profiling, rules, scorecards/metrics, exception workflows). Experience designing near real-time patterns (micro-batch/event-driven concepts) and handling late-arriving/out-of-order data. Familiarity with GCP operational practices for data workloads (service accounts/IAM basics, job monitoring, quota/cost controls). What the Hiring Manager Wants Suppliers to Focus On Please do not focus solely on job titles or keyword matching. What the candidate actually built What business problems they solved Their hands-on level of involvement The complexity of the environments they supported Experience with ETL development, data integration, and modernization efforts Ability to learn and adapt to new technologies Technical Environment Ab Initio ETL Design & Development Oracle Data Warehousing Data Modeling Programming Python PySpark PL/SQL SQL Unix Shell Scripting BigQuery Dataplex Migration from legacy data platforms to cloud-native solutions Scheduling & Orchestration AutoSys Airflow CI/CD & DevOps Jenkins uDeploy Git-based source control Automated testing and deployment Data Quality & Governance Data profiling and quality controls Data governance Metadata management Data classification and lineage Top Skills: Python In this contingent resource assignment, candidates may: Consult on or participate in moderately complex initiatives and deliverables within Software Engineering and contribute to large-scale planning related to Software Engineering deliverables. Review and analyze moderately complex Software Engineering challenges that require an in-depth evaluation of variable factors. Contribute to the resolution of moderately complex issues and consult with others to meet Software Engineering deliverables while leveraging solid understanding of the function, policies, procedures, and compliance requirements. Collaborate with client personnel in Software Engineering. Required Qualifications: 4 plus years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education. #J-18808-Ljbffr PTR Global