Director of Software Engineering - Data Platforms - #4919
Quick Summary
Our mission is to detect cancer early, when it can be cured. We are working to change the trajectory of cancer mortality and bring stakeholders together to adopt innovative, safe,
We are seeking a visionary and execution-focused Director of Software Engineering to lead our Data Platform engineering organization. In this role, you will drive the technical strategy, architecture, and delivery of our next-generation, cloud-native data platform.
The ideal candidate brings over 15 years of software engineering experience, combining deep technical expertise in big data, cloud infrastructure, and AI-driven workflows (including RAG and LLM applications) with a proven track record of scaling engineering teams (10+ headcount). You will collaborate closely with cross-functional executives to translate complex domain requirements into scalable, secure, and compliant production-grade software.
This role is based in Sunnyvale, California. It offers a flexible work arrangement, with the ability to work from GRAIL's office or from home. Our current flexible work arrangement policy requires that a minimum of 60%, or 24 hours, of your total work week be on-site. Your specific schedule, determined in collaboration with your manager, will align with team and business needs and could exceed the 60% requirement for the site. At our Sunnyvale campus, Tuesdays and Thursdays are the key days where we encourage on-site presence to engage in events and on-site activities but candidates must be flexible based on the needs of the business.
Team Scaling & Culture: Lead, mentor, and scale a multi-disciplinary global engineering organization, fostering a culture of high performance, continuous learning, and technical excellence.
Strategic Roadmap Delivery: Own the technical roadmap and resource allocation, ensuring 95%+ on-time execution of strategic product milestones.
Agile Transformation: Champion and mature Agile/Scrum methodologies to optimize feature velocity, minimize product turnaround time, and maintain high software quality.
Cloud-Native Evolution: Architect, govern, and optimize the transition to modern serverless and microservices architectures on AWS, driving structural cost optimization and system elasticity.
Big Data Ecosystems: Define the strategy for next-generation big data platforms utilizing Snowflake, Databricks, Apache Iceberg, AWS Glue, etc. to process, partition, and index petabyte-scale datasets.
Performance Engineering: Oversee analytical and search data model optimizations to continually improve query performance and data pipeline throughput.
AI-Driven Initiatives: Direct the integration of AI-assisted SDLC tools and architect LLM-enabled product features, including RAG-based semantic search and conversational search workflows.
API & System Interoperability: Oversee the development of high-throughput ETL pipelines and secure, scalable RESTful APIs built on Java / Spring Boot to ensure global data interoperability.
DevOps & SRE Practices: Mature CI/CD automation pipelines using infrastructure-as-code (Terraform, Ansible, Jenkins) to automate provisioning and security patching.
Security & Compliance: Ensure all platforms strictly adhere to modern cybersecurity standards and regulatory compliance frameworks (e.g., GDPR, HIPAA).
15+ years of progressive experience in software engineering, with 5+ years in a dedicated engineering leadership role managing cross-functional, global teams.
Proven ability to interface with executive stakeholders (Product, UX, Architecture) to align engineering outputs with business growth.
Strong experience managing large operational budgets and implementing strategic cloud cost-optimization practices.
Backend & Architecture: Expert-level knowledge of Java, Spring Boot, Spring MVC, distributed systems design, database sharding, and high-performance microservices.
Data & Analytics: Deep proficiency with Snowflake, Apache Iceberg, AWS Glue, Spark, and Elasticsearch.
AI & Search: Hands-on architecture experience with Retrieval-Augmented Generation (RAG), Large Language Model (LLM) frameworks, and semantic/conversational search.
Cloud & DevOps: Strong expertise in AWS Cloud infrastructure, containerization, and IaC tools (Terraform, Ansible, Jenkins).
Domain Interoperability: Experience in high-volume, regulated data fields (e.g., genomics, healthcare, bioinformatics, or fintech) and data standards (e.g., GA4GH) is highly desirable.
Master’s Degree in Computer Science, Software Engineering, or a highly related technical field preferred.
Bachelor’s Degree in Computer Science or Engineering or equivalent practical experience.
Location & Eligibility
Listing Details
- Posted
- July 29, 2026
- First seen
- July 29, 2026
- Last seen
- July 30, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 62%
- Scored at
- July 29, 2026
Signal breakdown
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