Power Platform Developer

Job Description:

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Role Overview:

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The Home Lending Data & Insights team supports the Home Mortgage organization by delivering enterprise data products and solutions.

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The team manages complex data ecosystems involving mortgage application processing, imaging platforms, loan processing systems, and other supporting mortgage applications.

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The selected consultant will primarily support the Core Downstream application, which receives and processes mortgage application data.

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This role is focused on consolidating data from multiple repositories, cleansing and transforming it, and delivering trusted data assets to business consumers.

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This is a hands-on Senior Data Engineer / ETL Developer role that combines traditional enterprise ETL development with cloud modernization initiatives.

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Team Environment:

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3 Scrum Teams

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1 U.S.-based team

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2 India-based teams

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Approximately 14 team members supporting the application

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Strong onboarding process and documentation in place to bring people up to speed

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Contractors currently work onsite five days per week

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Contract position with potential interest in future conversion

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Key Responsibilities:

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Build and maintain scalable batch and near real-time data pipelines

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Develop ETL solutions using Ab Initio, Python, PySpark, SQL and PL/SQL

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Review technical designs and convert solution blueprints into reusable code

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Integrate, cleanse, normalize, and transform data from multiple mortgage-related systems

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Partner with Product Owners, Architects, Engineers, and business stakeholders

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Support migration and modernization initiatives from legacy platforms to Google Cloud

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Build, schedule, orchestrate, and deploy solutions through enterprise CI/CD pipelines

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Support monitoring, operational excellence, root cause analysis, and production reliability

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Required Qualifications:

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4 plus years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

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4 plus years PL/SQL and SQL skills with proven experience in Oracle, Teradata, Python and/or BigQuery: complex query development, tuning, and debugging.

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4 plus years Ab Initio skills with proven experience to build complex graphs, Psets, performance tuning.

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3 plus years programming skills in Python; hands-on PySpark for distributed data processing

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3 plus years of ETL/ETL design, data warehousing concepts, and data modeling best practices

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Desired Qualifications:

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Financial Services or Mortgage industry experience

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Production operations experience: monitoring, SLAs, incident response, root cause analysis, and performance optimization.

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Experience working in hybrid environments (on-prem + cloud) and supporting data migration/modernization initiatives.

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Experience with scheduling/orchestration in Autosys and Airflow-based orchestration (Cloud Composer direction).

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Experience with Git-based workflows, code reviews, and automated testing practices for data pipelines.

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Experience with Harness, Jenkins and uDeploy based CICD environments.

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Practical experience using AI-assisted coding tools in daily development to improve productivity without compromising quality or security.

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Ab Initio development/maintenance experience and/or hands-on migration of Ab Initio graphs to modern Spark/SQL patterns.

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Experience with Dataplex and broader data governance concepts (metadata, classification, stewardship, lineage practices).

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Experience with Informatica Data Quality implementation patterns (profiling, rules, scorecards/metrics, exception workflows).

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Experience designing near real-time patterns (micro-batch/event-driven concepts) and handling late-arriving/out-of-order data.

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Familiarity with GCP operational practices for data workloads (service accounts/IAM basics, job monitoring, quota/cost controls).

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What the Hiring Manager Wants Suppliers to Focus On

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Please do not focus solely on job titles or keyword matching.

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Instead, evaluate:

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What the candidate actually built

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What business problems they solved

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Their hands-on level of involvement

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The complexity of the environments they supported

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Experience with ETL development, data integration, and modernization efforts

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Ability to learn and adapt to new technologies

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Technical Environment

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Data Engineering & ETL

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Ab Initio

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ETL Design & Development

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Oracle

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Teradata

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Data Warehousing

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Data Modeling

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Programming

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Python

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PySpark

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PL/SQL

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SQL

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Unix Shell Scripting

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Cloud & Modernization

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Google Cloud Platform (GCP)

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BigQuery

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Dataplex

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Migration from legacy data platforms to cloud-native solutions

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Scheduling & Orchestration

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AutoSys

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Airflow

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Google Cloud Composer

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CI/CD & DevOps

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Jenkins

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Harness

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uDeploy

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Git-based source control

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Automated testing and deployment

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Data Quality & Governance

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Informatica Data Quality

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Data profiling and quality controls

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Data governance

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Metadata management

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Data classification and lineage

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Top Skills:

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Ab Initio & Unix Shell

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Python

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CI/CD

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In this contingent resource assignment, candidates may:

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Consult on or participate in moderately complex initiatives and deliverables within Software Engineering and contribute to large-scale planning related to Software Engineering deliverables.

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Review and analyze moderately complex Software Engineering challenges that require an in-depth evaluation of variable factors.

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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.

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Collaborate with client personnel in Software Engineering.

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Required Qualifications:

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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.