Ab Initio Developer

Role: Ab Initio Developer

Charlotte NC- 5 Days ONSITE 

2 Round Interviews - Teams

2-year duration

Key Skills: Abinitio, Python, PL/SQL, Teradata, BigQuery (preferred)

CI/CD, Orchestration, Airflow, Unix Shell Scripting exp

Position highlights: 

Data Engineering aligned with Home lending line of business

Designing Blueprints

Data modeling and analysis exp required

Data transformation and distribution

Interact with complex system

Should have sourced data from large complex systems

ETL/ETL experience for few years

Financial Services exp preferred or can consider large Enterprise Clients

Strong Python programming experience

Job Description:
About this role:

• Join the Home Lending Data and Insights team as a Software Engineer 3 - Contingent, where candidates will build, run, and modernize enterprise data pipelines in a hybrid landscape—spanning on?prem platforms (Python, Oracle, Teradata and Ab Initio) and a modern Google Cloud stack (BigQuery, Dataplex).
• Candidates will focus on dependable batch and near real-time processing, operational excellence, and the transition from legacy scheduling and ETL patterns to cloud-native orchestration with Google Cloud Composer, backed by strong data quality standards using Informatica Data Quality.

In this role, candidates will:

• Build and maintain scalable batch and near real-time data pipelines using AB Initio, Python, PySpark, PL / SQL and SQL to ingest, transform, and publish curated datasets across on-prem and Google Cloud platforms.
• Develop and optimize BigQuery transformations and data models, including partitioning, clustering, query optimization, and cost/performance tuning.
• Support modernization/migration from Teradata and Ab Initio workflows to Google Cloud Platform/BigQuery, including logic re-platforming, reconciliation, parallel runs, and controlled cutovers.
• Implement orchestration and scheduling for pipelines using legacy Autosys while driving migration toward Google Cloud Composer (Airflow), including dependency management, retries, SLAs, and backfills.
• Apply data governance and discovery practices using Dataplex: metadata management, dataset organization, classification support, and ensuring data is consumption-ready.
• Build and operationalize data quality controls using Informatica Data Quality: profiling, rule implementation, thresholds, exception handling, and embedding quality gates into pipelines.
• Ensure operational excellence: monitoring, alerting, runbooks, incident triage/root cause analysis, and continuous improvements to reliability and performance.
• Implement secure data engineering practices: least-privilege access, PII handling/masking where required, retention controls, and audit-friendly documentation.
• Partner with product, analytics, and engineering stakeholders to translate requirements into clear data contracts, curated datasets, and maintainable documentation (data dictionaries, reconciliation notes, operational runbooks).

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.
• Closely partner with Product Owners, Architects and Engineers on definition, design, development, integration, testing and support of reliable and reusable Data pipelines.
• Analyze highly complex business requirements; generate technical specifications to design ETL processes.
• Act as an expert technical resource for analysis and provides critical direction to less experienced staff. Work with team members to provide insight into solving complex problems with middleware while leveraging enterprise and industry best practices (including scalability, availability, maintainability, and flexibility).