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.
• Determine and pursue courses of action necessary to obtain desired results.
• Work on unusually complex technical problems and provide solutions which are highly innovative and ingenious.
• Develops and applies complex and often long-term strategies on specific projects.
• Act as the technical expert to be sought for guidance on new technology direction.
• Lead the architecture and delivery of core data platform capabilities, including ingestion, transformation, metadata, governed access, data quality, and analytics-ready data layers.
• Ensure platform capabilities are built for long-term scale, reuse, governance, and AI enablement from day one.

Stakeholder Management & Cross-Functional Collaboration:

• Translates overall direction and strategy and communicates across organizational levels, to influence executives when needed.
• Leads strategic initiatives and ensure successful executions.
• Act as organization spokesperson on advanced projects and/or programs.
• Acts as advisor to management and customers on advanced technical research studies and applications.
• Interacts with senior external personnel on significant technical matters often requiring coordination between organizations.
• Partners closely with platform engineering, governance, security, and domain teams to define platform standards and scalable implementation patterns.
• Helps align business, data, and technical stakeholders around a common platform vision and architecture.

Operational Excellence, Quality & Compliance:

• Own the oversight of documentation of infrastructure and work instructions for systems and applications.
• Develop approaches and implement solutions to mitigate future incidents.
• Ensure that completed work delivers long-term value and enhances platform performance to maintain maximum functionality.
• Make decisions regarding access, permissions, and security controls across systems.
• Establish standards for metadata, data quality, governance, and platform reliability that improve trust, auditability, and enterprise reuse.
• Ensure that governance, compliance, and security are built into the platform architecture and operating model.

Subject Matter Expertise:

• Serve as the SME for general engineering issues and platform strategy.
• Mentor and coach engineers across the team, fostering technical excellence.
• Keep abreast of industry trends and evaluate platform needs for future growth.
• Bring strong ownership, clarity of thought, and architectural judgment to platform design and decision-making.

SUPERVISORY RESPONSIBILITIES:

• No supervisory responsibilities.

Education:
EDUCATION/EXPERIENCE/KNOWLEDGE & SKILLS:

• Master's degree in a relevant field and 9 years of experience; or
• Bachelor's degree in a relevant field and 11 years of related experience; or
• Equivalent combination of education or years of experience.
• Technical certification may be required.

Experience:

• At least 10 years of experience in cloud infrastructure and/or enterprise data platforms in a highly available and production environment.
• Experience working in a SOX and FDA regulated environment is a plus.
• Life sciences experience is a strong plus.

Knowledge, Skills And Abilities:

• Advanced level knowledge of Amazon Web Services (AWS), especially with services related to data storage, data processing, analytics, security, and compute.
• Advanced level knowledge with infrastructure as code (IaC) tools, especially Terraform.
• Intermediate level knowledge with cloud and infrastructure automation.
• Intermediate level knowledge of modern development and deployment practices of continuous integration and continuous deployment.
• Strong knowledge of Databricks, modern lakehouse architecture, governance, metadata, and data quality principles.
• Strong working knowledge of Python, SQL, Spark, and dbt.
• Strong ability to design scalable, governed, and reusable data platform capabilities that support analytics and AI.

#LI-EZ1

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The base pay range for this position is $182,000 - $259,000 annually. The base pay range may take into account the candidate's geographic region, which will adjust the pay depending on the specific work location. The base pay offered will take into account the candidate's geographic region, job-related knowledge, skills, experience and internal equity, among other factors.

In addition to the base salary, as part of our Total Rewards program, Exelixis offers comprehensive employee benefits package, including a 401k plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts. Employees are also eligible for a discretionary annual bonus program, or if field sales staff, a sales-based incentive plan. Exelixis also offers employees the opportunity to purchase company stock, and receive long-term incentives, 15 accrued vacation days in their first year, 17 paid holidays including a company-wide winter shutdown in December, and up to 10 sick days throughout the calendar year.

DISCLAIMER
The preceding job description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to the job.