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.

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