Ab Initio Developer

PERI - OPERATIVE STAFFING SOLUTIONS, LLC
Charlotte, United States of America
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Charlotte, United States of America

Tech stack

Artificial Intelligence
Airflow
CA Workload Automation Ae
Google BigQuery
Cloud Computing
Cloud Database
Cloud Engineering
Code Review
Data Validation
Data Dictionary
Data Discovery
Information Engineering
Data Governance
Data Infrastructure
Data Integration
ETL
Data Masking
Data Transformation
Data Security
Data Warehousing
Programming Tools
Dimensional Modeling
Information Lifecycle Management
Python
Meta-Data Management
Oracle
Oracle Applications
Performance Tuning
Query Optimization
Software Tools
Secure Coding
PL-SQL
SQL Databases
Teradata
Enterprise Data Management
Google Cloud Platform
GitHub Copilot
Parallel Computation
Reliability of Systems
Ab Initio
GIT
PySpark
Google BigQuery
Stream Processing
Data Pipelines

Job description

We are seeking an experienced Ab Initio Developer to join the Home Lending Data & Insights team. This role focuses on designing, developing, and modernizing enterprise data pipelines across both legacy on-premises platforms and Google Cloud Platform (Google Cloud Platform). The ideal candidate has strong expertise in ETL development, cloud data engineering, and enterprise-scale data modernization, with experience supporting highly available, production-grade data environments.

You will help migrate legacy Teradata and Ab Initio solutions to cloud-native architectures while ensuring data quality, operational excellence, security, and scalability., * Design, develop, and maintain scalable batch and near real-time data pipelines using Ab Initio, Python, PySpark, PL/SQL, and SQL.

  • Build and optimize Google BigQuery datasets, transformations, and data models using partitioning, clustering, and query optimization techniques.
  • Support migration initiatives from Teradata and Ab Initio to Google Cloud Platform, including data validation, reconciliation, parallel processing, and production cutovers.
  • Develop and maintain workflow orchestration using Autosys, while driving modernization to Google Cloud Composer (Apache Airflow).
  • Implement metadata management, governance, and data discovery using Google Dataplex.
  • Build and maintain enterprise data quality controls using Informatica Data Quality, including profiling, validation rules, exception handling, and quality monitoring.
  • Monitor production pipelines, troubleshoot failures, perform root cause analysis, and implement continuous improvements to system reliability and performance.
  • Apply secure data engineering practices including PII protection, data masking, access controls, retention policies, and audit documentation.
  • Partner with Product Owners, Architects, Analysts, and Engineering teams to define technical solutions and deliver curated, trusted datasets.
  • Create and maintain technical documentation including data dictionaries, reconciliation documents, operational runbooks, and technical specifications.
  • Utilize AI-assisted development tools such as GitHub Copilot, Devin, or similar to improve engineering productivity while maintaining secure coding practices, code reviews, and testing standards.
  • Provide technical leadership and mentor junior engineers by promoting engineering best practices and scalable solution design.
  • Analyze complex business requirements and translate them into robust ETL and data engineering solutions.

Requirements

  • 4+ years of professional Data Engineering experience.
  • 4+ years of experience with PL/SQL and SQL, including complex query development, optimization, and troubleshooting.
  • Hands-on experience with Oracle, Teradata, Python, and/or Google BigQuery.
  • 4+ years of experience developing enterprise ETL solutions using Ab Initio, including graph development, Psets, and performance tuning.
  • 3+ years of experience programming in Python with hands-on PySpark development.
  • 3+ years of experience with ETL architecture, data warehousing concepts, dimensional modeling, and data integration best practices.
  • Experience building scalable batch and near real-time data processing solutions.
  • Strong understanding of enterprise data governance, metadata management, and data lifecycle management.
  • Must-have: Use AI-assisted coding tools (e.g., GitHub Copilot, Devin, or similar) to accelerate development while maintaining strong code review discipline, testing, and secure coding standards

Preferred Qualifications

  • Experience with Google Cloud Platform (Google Cloud Platform) services including:
  • BigQuery
  • Dataplex
  • Google Cloud Composer (Apache Airflow)
  • Experience migrating enterprise data platforms from on-premises environments to cloud-native architectures.
  • Experience with Informatica Data Quality (IDQ).
  • Familiarity with Autosys scheduling and workload automation.
  • Experience implementing secure data engineering practices for regulated environments.
  • Experience using AI-assisted software development tools such as GitHub Copilot or Devin.
  • Experience working in Agile/Scrum environments.
  • Financial services or mortgage/lending industry experience is a plus.

Technical Environment

  • Languages: Python, PySpark, SQL, PL/SQL
  • ETL: Ab Initio
  • Databases: Oracle, Teradata, BigQuery
  • Cloud: Google Cloud Platform (BigQuery, Dataplex, Cloud Composer)
  • Scheduling: Autosys, Apache Airflow (Cloud Composer)
  • Data Quality: Informatica Data Quality
  • Development Tools: GitHub Copilot, Devin, Git

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