Design, build, and operate scalable data science and analytics solutions that power business decision-making and digital products. This role bridges data science development, distributed data processing, and cloud platform engineering – ensuring that models, rules, and analytics workflows are performant, secure, observable, and production-ready on enterprise cloud platforms.

WHAT I DO – Key Accountabilities :

– Design and develop Spark based (PySpark) modules implementing custom data science logic, statistical methods, and complex business rules.

– Build reusable, scalable Python and SQL components for batch and near real-time analytics workloads.

– Optimize data pipelines for performance, reliability, and cost efficiency across large datasets.

– Translate analytical and data science requirements into production-grade, testable code.

Data Science Platform & Cloud Enablement :

– Contribute to and support the Applied Data Science hosting Spark workloads and web applications on GCP and/or Azure.

– Configure and manage cloud resources including :

i. Virtual Private Clouds (VPCs) and networking

ii. Secure access patterns and Role-Based Access Control (RBAC)

iii. IP whitelisting and external exposure of applications

– Enable observability through logging, monitoring, alerting, and traceability for both data and application workloads.

Infrastructure, CI/CD & Automation :

– Implement and maintain CI/CD pipelines for data science and Spark workloads.

– Use Docker for containerized execution and deployment.

– Apply Terraform / IaC principles to provision and manage cloud infrastructure.

– Ensure consistent, repeatable deployments across development, staging, and production environments.

Engineering Quality & Governance :

– Enforce best practices around code quality, testing, version control, and documentation.

– Partner with security and platform teams to ensure compliance with enterprise standards.

– Troubleshoot production issues across data pipelines, Spark jobs, and platform components.

Collaboration & Technical Leadership :

– Work closely with Data Scientists, ML Engineers, Platform Engineers, and Product teams to operationalize analytics solutions.

– Provide technical guidance and reviews for complex data science engineering work.

– Contribute to platform standards, reusable frameworks, and engineering roadmaps.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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