Technical Product Manager

At Veracyte, we offer exciting career opportunities for those interested in joining a pioneering team that is committed to transforming cancer care for patients across the globe. Working at Veracyte enables our employees to not only make a meaningful impact on the lives of patients, but to also learn and grow within a purpose driven environment. This is what we call the Veracyte way – it’s about how we work together, guided by our values, to give clinicians the insights they need to help patients make life-changing decisions. 

Our Values:

• We Seek A Better Way: We innovate boldly, learn from our setbacks, and are resilient in our pursuit to transform cancer care
• We Make It Happen: We act with urgency, commit to quality, and bring fun to our hard work
• We Are Stronger Together: We collaborate openly, seek to understand, and celebrate our wins
• We Care Deeply: We embrace our differences, do the right thing, and encourage each other

The Position:

The Technical Product Manager (TPM) on the Veracyte Data Engineering team will lead the product strategy, development, and lifecycle management of data engineering solutions, including the Veracyte Lakehouse and related data cataloging initiatives. This role bridges technical and business needs, collaborating with data engineers, data scientists, and cross-functional teams in a Scrum environment to deliver scalable, secure, and innovative data products aligned with Veracyte’s global data strategy and digital transformation goals.

This position is based out of our San Diego office (hybrid) and we are open to remote (US, PST ideal).

Key Responsibilities:

1. Define and Execute Product Vision:
• Develop and maintain the product roadmap and backlog for data engineering solutions, prioritizing features based on business value, user needs, and technical feasibility.
• Serve as the Scrum Product Owner, managing the team’s unified backlog and ensuring alignment with organizational objectives.
2. Collaborate Across Teams:
• Work with data engineers, data scientists, and stakeholders to gather requirements, translate them into user stories, and oversee their implementation via Jira.
• Facilitate backlog grooming, sprint planning, and daily stand-up meetings to drive team progress.
3. Conduct Research and Analysis:
• Perform market and competitive analysis to identify opportunities for enhancing data infrastructure, pipelines, and cataloging tools.
• Gather user feedback to refine data products and ensure they meet the needs of technical and non-technical audiences.
4. Oversee Data Management and Governance:
• Ensure data engineering solutions comply with data governance policies, security standards, and regulatory requirements.
• Support the design and implementation of a data catalog framework, leveraging tools and best practices for data source discovery and accessibility.
5. Drive Data Strategy and Innovation:
• Collaborate with leadership to align data engineering initiatives with Veracyte’s overall data and digital strategies.
• Recommend best practices for scalability, security, and usability in data products, including integration with AWS, Snowflake, and open formats like Apache Parquet.
• Provide training and documentation for internal teams and stakeholders on data engineering tools and processes.
6. Mentorship and Collaboration:
• Mentor junior product team members and foster cross-disciplinary collaboration to promote innovation and continuous improvement.
• Act as a liaison between technical teams and business units to ensure successful product delivery.

Who You Are:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Experience:
• 5+ years of experience in product management, with a focus on technical products in data engineering, cloud services, or software development.
• Experience working in a Scrum environment as a Product Owner is highly desirable.
• Technical Skills:
• Familiarity with data engineering concepts, including data lakes, pipelines, and cataloging tools.
• Understanding of cloud platforms (e.g., AWS, GCP) and data warehousing solutions (e.g., Snowflake).
• Basic knowledge of programming languages (e.g., Python, SQL) and data modeling is a plus.
• Soft Skills:
• Strong analytical and problem-solving skills