Ab Initio Developer

Strategic Staffing Solutions; Charlotte (NC); Hybrid; USD 110,000 - 150,000; Full time

Job summary

Strategic Staffing Solutions seeks an Ab Initio Developer to design, develop, and modernize data pipelines across on-premises and Google Cloud Platform. You will migrate legacy Teradata and Ab Initio solutions, ensure data quality, security, and scalability, and lead data-engineering efforts with modern orchestration and governance.

The role emphasizes ETL development, BigQuery modeling, and collaboration with cross-functional teams to deliver trusted datasets and production-grade pipelines.

Qualifications

• 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

Responsibilities

• Design, develop, and maintain scalable 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.

Skills

ETL development

Cloud data engineering

Data pipelines

Data governance

AI-assisted coding

Tools

Ab Initio

Python

PySpark

PL/SQL

SQL

Oracle

Teradata

BigQuery

Autosys

Apache Airflow

Dataplex

Informatica Data Quality

GitHub Copilot

Devin

Job description

Ab Initio Developer

Location: Charlotte, NC (Hybrid)
Duration: 24-Month Contract

Overview

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 (GCP). 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.

Key Responsibilities

• 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.

Required Qualifications

• 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 (GCP) 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