Location: Charlotte, NC
Salary: $53.00 USD Hourly - $57.00 USD Hourly
Description: Our client is currently seeking a ETL Ab Initio Production Support and Engineering candidate.
We are not considering Corp to Corp or 1099 candidates for this roleSoftware Engineer - ETL / Data Engineering (Ab Initio, PySpark, Python, Oracle)Location: Charlotte, NC 28202 or Charlotte, NC 28262 (Hybrid)
Duration: 12+ Month Contract (Potential Extension)
Employment Type: W2 Contract
About the RoleWe are seeking a Senior Software Engineer with deep expertise in ETL development, data integration, and large-scale data processing. This role will focus on supporting existing enterprise data platforms, modernizing legacy ETL solutions, and leading migration initiatives from Ab Initio to PySpark-based frameworks. The ideal candidate brings strong technical expertise in Python, Oracle Database, and data engineering best practices while operating effectively within an Agile environment.
This position requires a hands-on engineer who can partner with business and technology stakeholders to design, build, optimize, and support enterprise data solutions that are scalable, reliable, and aligned with strategic modernization objectives.
Responsibilities- Design, develop, maintain, and enhance enterprise ETL and data integration solutions.
- Provide production support for critical data processing applications, including incident resolution, troubleshooting, and root cause analysis.
- Develop and optimize data pipelines using Ab Initio, PySpark, Python, and Oracle technologies.
- Analyze existing ETL workflows and recommend modernization opportunities.
- Lead migration efforts from legacy ETL frameworks, including Ab Initio, to modern PySpark-based architectures.
- Collaborate with business analysts, architects, data engineers, and application teams to gather requirements and deliver high-quality solutions.
- Create technical design documentation, support procedures, and operational runbooks.
- Ensure data quality, performance optimization, and adherence to enterprise standards.
- Participate in Agile ceremonies, sprint planning, code reviews, and release activities.
- Utilize AI-assisted development tools such as GitHub Copilot, Microsoft Copilot, or equivalent solutions to improve productivity, code quality, testing, and documentation.
Minimum Qualifications- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience.
- 4+ years of experience in ETL development, data integration, or data engineering.
- Hands-on experience with:
- Ab Initio
- PySpark
- Python
- Oracle Database
- Strong SQL development and query optimization skills.
- Experience supporting enterprise-scale batch and data processing applications.
- Experience with production support, issue triage, incident management, and root cause analysis.
- Knowledge of software development lifecycle (SDLC) processes and best practices.
- Excellent analytical, troubleshooting, and communication skills.
Preferred Qualifications- Experience migrating ETL workloads from legacy platforms to modern data engineering frameworks.
- Experience with cloud-based data platforms and distributed data processing environments.
- Knowledge of DevOps practices, CI/CD pipelines, source control systems, and automated testing.
- Experience working in Agile/Scrum delivery models.
- Familiarity with data governance, data quality, and operational excellence practices.
- Experience leveraging AI-powered development and productivity tools.
- Ability to work independently while effectively collaborating across cross-functional teams.
Required Technical SkillsETL & Data Engineering- ETL Development
- Data Integration
- Data Pipeline Design
- Data Transformation
- ETL Modernization
Programming & Databases- PySpark
- Python
- Oracle Database
- SQL
Platforms & Tools- Ab Initio
- Git/Version Control
- CI/CD Tools
- AI-Assisted Development Tools
Methodologies- Agile/Scrum
- Production Support
- Incident Management
- Root Cause Analysis
Nice-to-Have Skills- Hadoop Ecosystem
- Spark Optimization
- AWS, Azure, or Google Cloud Platform
- Data Warehousing Concepts
- Performance Tuning
- Automated Testing Frameworks
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