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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Ab Initio Developer - **Company:** PERI - OPERATIVE STAFFING SOLUTIONS, LLC - **Location:** Charlotte, NC, United States - **Experience:** Experienced - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Airflow, CA Workload Automation Ae, BigQuery, Cloud Computing, Cloud Database, Cloud Engineering, Code Review, Data Validation, Data Dictionary, Data Discovery, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Masking, Data Transformation, Data Security, Data Warehousing, Programming Tools, Dimensional Modeling, Information Lifecycle Management, Python (Programming Language), Meta-Data Management, Oracle Databases, Oracle (Applications), Performance Tuning, Query Optimization, Software Tools, Secure Coding, PL-SQL, SQL Databases, Teradata SQL, Enterprise Data Management, Google Cloud, GitHub Copilot, Parallel Computation, Reliability of Systems, Ab Initio, Git, Pyspark, Google Bigquery, Stream Processing, Data Pipelines - **Published:** August 5, 2026 - **Apply:** https://www.dice.com/job-detail/74000434-0b1d-4ca0-af0a-ea3430bac92a ## About the Role * 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 ## 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Got AI ideas but no money? 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