Lead Python Architect: AI-Driven Data Pipelines & Cloud

OpenText; Richmond (VA); On-site; USD 150,000 - 190,000; Full time

Job summary

OpenText is seeking a Lead Python Developer to propel data pipelines and optimize data intake within the SCA data science team in the United States. You will guide architectural decisions, mentor teammates, and deliver scalable, high-quality data solutions across distributed teams in Sweden and India.

With 8+ years in software development and 5+ years in Python, you will drive AI/ML innovation, ensure robust testing, and craft resilient data architectures.

Qualifications

• 8+ years of software development experience with at least 5 years in Python focused on data pipelines and data quality.
• Expert-level Python development with clean architecture and rigorous testing (unit, integration).
• Proficient with ML/AI libraries in Python for prototyping and production use.
• Experience leading developers, coaching juniors, and owning technical decisions.
• Strong database and schema design skills for complex data models.

Responsibilities

• Lead the data pipelines and optimize data intake processes.
• Collaborate with cross-geo teams to deliver data-driven solutions.
• Prototype AI/LLM solutions and scale them into production while balancing cost/value.
• Maintain and improve data quality to enhance OpenText SCA analysis and product competitiveness.

Skills

Leadership

Collaboration

Data quality

Software architecture

Testing (unit/integration)

Education

Bachelor's degree in Computer Science

Tools

Python

Kubernetes

CI/CD

Elasticsearch

Neo4j

GCP

ML libraries

Job description

OpenText is seeking a Lead Python Developer to propel data pipelines and optimize data intake within the SCA data science team in the United States. You will guide architectural decisions, mentor teammates, and deliver scalable, high-quality data solutions across distributed teams in Sweden and India.

With 8+ years in software development and 5+ years in Python, you will drive AI/ML innovation, ensure robust testing, and craft resilient data architectures.