Senior DS Platform Developer

Proudly founded in Australia, we are a global energy company providing reliable and affordable energy to help people lead better lives. Woodside Global Solutions in Bengaluru brings together talent, digital expertise and operational excellence to support Woodside's global operations.

Woodside Global Solutions in Bengaluru is being built as a hub of excellence, to drive innovation and global collaboration. We are looking for talented professionals who are eager to make a global impact, helping to shape the future of Woodside together.

The Senior Data Science Platform Developer is responsible for designing, building, and maintaining core platform components that enable scalable, secure, and reliable data science development and deployment across the enterprise.

This role focuses on platform automation, and the integration of data science tools and frameworks (such as Posit Workbench, Github, AWS SageMaker, and various custom-built systems).

Working closely with the Data Science Platform Lead and Cloud Engineering teams, the developer ensures platform reliability, performance, and compliance—empowering data scientists to build, deploy, and manage models efficiently within governed environments.

Safety & Operational Excellence

• Apply secure coding and deployment practices, adhering to cybersecurity, access control, and compliance frameworks.
• Implement automated patching, monitoring, and logging for platform reliability and auditability.
• Promote infrastructure resilience and disaster recovery readiness through backup and recovery automation.

Technical Delivery

• Develop and maintain reusable platform components for data science workflows, including environment provisioning, package management, and CI/CD pipelines.
• Automate provisioning and updating of Posit Workbench, Posit Connect, and Posit Package Manager environments.
• Integrate data science tools with AWS services such as S3, ECR, CodeBuild, SageMaker, and Secrets Manager.
• Build APIs and automation scripts to simplify onboarding, environment lifecycle management, and access control.
• Implement monitoring and observability solutions using CloudWatch, Datadog, and log aggregation tools.
• Contribute to cost optimization through resource tagging, utilization tracking, and anomaly detection.
• Document infrastructure, automation, and operational procedures.

Collaboration

• Partner with Data Science Lead to ensure alignment with enterprise architecture and governance.
• Collaborate with data scientists to understand environment needs, dependencies, and tooling requirements.
• Work with Cybersecurity and IAM teams to maintain compliance and minimise change impact.
• Contribute to peer code reviews, platform design discussions, and continuous improvement initiatives.
• Support knowledge sharing by maintaining internal documentation, tutorials, and platform user guides.

Key Accountabilities

• Delivery of secure, automated, and scalable data science platform environments.
• Compliance with Woodside’s enterprise standards and cybersecurity policies.
• Reliable CI/CD pipelines for data science models and applications.
• Effective collaboration with Cloud, Data, and AI teams to enable efficient model deployment.

Technical Skills / Experience:

• Bachelor’s degree in Computer Science, Engineering, or a related technical field.
• 10+ years of experience in platform development, DevOps, or cloud engineering, ideally supporting data science or analytics workloads.
• Proficiency with AWS services (S3, EFS, EC2, ECR, Lambda, SageMaker, Secrets Manager, RDS, DynamoDB, CodeBuild, Service Catalog, SQS, SNS).
• Experience with Linux distributions (Debian, Ubuntu).
• Strong scripting and automation skills in Python and Bash.
• Experience with containerization (Docker, Kubernetes, ECS) and IaC tools (Terraform, CloudFormation).
• Familiarity with data science tools such as VS Code, Jupyter Notebook / JupyterLab, Posit Workbench (RStudio), and MLflow.
• Experience integrating identity and security frameworks (SSO, LDAP, IAM roles, MFA, OAuth2.0).
• Understanding of CI/CD principles, Git-based workflows, and automated testing frameworks.
• Experience with monitoring tools (Datadog, CloudWatch) and log pipelines.
• Awareness of Responsible AI, data governance, and cloud compliance standards.