SUMMARY/JOB PURPOSE:

The Associate Principal Engineer – Cloud Platform will support the design and creation of cloud-based products and services to meet the technology needs of Exelixis.   This position will help define and design our cloud platform, which includes cloud automation tools and standards, CI/CD pipelines, DevOps tooling and AWS account provisioning automation.  This position will also work with application support teams to re-define the interface between our cloud platform products and application installation and configuration processes. 

ESSENTIAL TECHNICAL DUTIES AND RESPONSIBILITIES:

• Create and lead the implementation of robust, scalable, and secure data architecture strategies on AWS and Databricks to support advanced analytics and AI/ML initiatives.
• Design and implement data ingestion, processing, storage, and reporting solutions leveraging AWS services like S3, Glue, Redshift, Lake Formation, Athena, Kinesis, MSK, EC2, ECS, and Databricks.
• Provide expert guidance and hands-on development on the AWS and Databricks data technologies.
• Develop and maintain conceptual, logical, and physical data models, and design data lakes, data warehouses, and analytics-ready data layers for optimal performance, reuse, and scalability.
• Establish and enforce data governance policies, data quality standards, security protocols, and compliance frameworks (e.g., FAIR, GxP, HIPAA, IAM, Data Mesh).
• Implement and manage AWS Lake Formation and Databricks Unity Catalog to enable centralized, fine-grained data governance across all data assets.
• Design and develop scalable and resilient application compute infrastructure using AWS EKS and ECS.
• Lead the development of automated CI/CD pipelines for notebooks, jobs, and infrastructure-as-code for AWS, dbt, and Databricks environments.
• Utilize tools like GitHub Actions or Jenkins to automate deployments and promote consistent releases.
• Manage and optimize AWS, Databricks, and other data platform resource utilization to maintain cost-effectiveness.
• Design and implement a multi-layered Medallion architecture (Bronze, Silver, Gold) using Delta Lake to ensure data quality and reliability.
• Define and develop reusable, governed data products that power analytics and AI use cases across the enterprise.
• Apply AI in a practical way as part of the platform, including services such as AWS Bedrock, where appropriate, to improve platform capabilities and data consumption experiences.
• Develop and publish data engineering best practices and patterns.

Experience:

EXPERIENCE/KNOWLEDGE & SKILLS:

• Proven experience architecting and implementing lakehouse architectures on AWS data technologies (Glue, Lake Formation, Redshift, Athena) and Databricks.
• Proven experience designing, developing, and managing data engineering pipelines at scale.
• Expertise in various data modeling techniques (conceptual, logical, and physical).
• Expertise in programming languages and frameworks such as dbt, Python, Spark SQL, and SQL.
• Deep knowledge of AWS services, including IAM, security, data storage, data processing, compute, and analytics services.
• Strong understanding of modern data architecture patterns (e.g., data mesh, lakehouse).
• Hands-on experience with big data technologies like Apache Spark, AWS Glue, Databricks, Apache Iceberg, and Delta Tables.
• Strong understanding of governance, metadata, data quality, and scalable platform design for enterprise data platforms.
• Experience building data platforms end-to-end, not just supporting existing environments.
• Experience applying AI or GenAI in real systems is highly valued.
• Certifications: Professional AWS and Databricks certifications are highly valued and relevant.

ESSENTIAL DUTIES/RESPONSIBILITIES:

Product Strategy & Product Road Map:

• Supports the translation of overall direction and strategy and communicates across organizational levels and functions.
• Works toward long-range goals and objectives.
• Assignments are primarily self-initiated.
• Understands key business processes and business areas.
• Acts as resource and provides direction to others.
• Helps define and evolve the enterprise data and analytics platform strategy and roadmap, with a focus on governed data access, reusable data products, self-service enablement, and AI readiness.

Product Development & Delivery:

• Guides the successful completion of major initiatives or programs and leads large complex projects.
• Refine end-to-end development processes, from ideation through CI/CD, security scanning, and production monitoring.
• Determin