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Data Infrastructure Manager information

What are the key skills and qualifications needed to thrive as a Data Infrastructure Manager, and why are they important?

To thrive as a Data Infrastructure Manager, you need expertise in data architecture, storage solutions, and database administration, typically backed by a degree in computer science or a related field. Familiarity with tools like SQL, Hadoop, cloud platforms (AWS, Azure, or Google Cloud), and certifications such as AWS Certified Solutions Architect are highly valuable. Strong leadership, problem-solving, and communication skills help you effectively manage teams and collaborate with stakeholders. These skills and qualities ensure reliable, scalable data systems that support organizational goals and data-driven decision making.

What is the difference between Data Infrastructure Manager vs Data Engineer?

AspectData Infrastructure ManagerData Engineer
Primary FocusOversees data systems, infrastructure, and architecture managementBuilds, develops, and maintains data pipelines and models
Required SkillsData architecture, leadership, project managementProgramming, ETL processes, database management
CertificationsCloud certifications, data management certificationsSQL, Python, cloud platform certifications
Work EnvironmentManagement, strategic planning, cross-team collaborationHands-on coding, data pipeline development

The Data Infrastructure Manager focuses on overseeing and managing the company's data systems and architecture, ensuring data availability and security. In contrast, Data Engineers are primarily responsible for designing and building the data pipelines and tools needed for data analysis. Both roles require technical skills and certifications, but the Manager role emphasizes leadership and strategic oversight, while the Engineer role is more technical and implementation-focused.

What are Data Infrastructure Managers?

Data Infrastructure Managers are professionals responsible for overseeing the design, implementation, and maintenance of an organization's data systems and architecture. They ensure that data storage, processing, and retrieval systems are efficient, secure, and scalable to meet business needs. Their role typically involves managing a team of data engineers, collaborating with IT and business units, and setting strategies for data governance and compliance. Data Infrastructure Managers play a critical role in enabling reliable data analytics and business intelligence by maintaining robust data pipelines and platforms.

What are some common challenges faced by Data Infrastructure Managers, and how can they be addressed?

Data Infrastructure Managers often encounter challenges such as scaling systems to handle increasing data volumes, ensuring high availability, and integrating new technologies with legacy systems. Addressing these issues typically involves proactive capacity planning, implementing robust monitoring and alerting tools, and fostering cross-functional collaboration with data engineering and IT security teams. Staying up-to-date with industry best practices and investing in staff training can also help mitigate these challenges and ensure reliable, scalable infrastructure.
What are the most commonly searched types of Data Infrastructure jobs in California? The most popular types of Data Infrastructure jobs in California are:
What are popular job titles related to Data Infrastructure Manager jobs in California? For Data Infrastructure Manager jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Infrastructure Manager jobs in California look for? The top searched job categories for Data Infrastructure Manager jobs in California are:
What cities in California are hiring for Data Infrastructure Manager jobs? Cities in California with the most Data Infrastructure Manager job openings:
Data Infrastructure Manager jobs near you
Infographic showing various Data Infrastructure Manager job openings in California as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Software Engineer, Data Infrastructure

Software Engineer, Data Infrastructure

Intrinsic

Mountain View, CA

$147K - $200K/yr

Other

Posted 26 days ago

Job description

Software Engineer, Data Infrastructure

Mountain View, California

Intrinsic is an AI robotics group at Google aiming to reimagine the potential of industrial robotics. Our team believes that advances in AI, perception and simulation will redefine what's possible for industrial robotics in the near future – with software and data at the core.

Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers. We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics.

Role

As a Software Engineer on the Data Infrastructure team, you will be responsible for designing, building, and maintaining the data infrastructure that powers our cutting-edge robotics systems. Your software will enable design, development, and operational robotic workflows, integrating with Kubernetes based cloud and on-device services. This includes the systems that collect and process data from our robots in the real world, and feed that data into our machine learning pipelines to train and evaluate the models that make our robots intelligent. You will collaborate with a passionate Product and Engineering team creating software that enables fleets of robots to build better.

How Your Work Moves the Mission Forward
  • Design, develop, and maintain scalable and reliable data pipelines for collecting, processing, and storing large volumes of robotics data (e.g., sensor data, telemetry, logs).
  • Build Data pipelines to train the next generation of functional robot models.
  • Build and maintain tools and infrastructure for data exploration, analysis, and visualization.
  • Implement and maintain data security and privacy best practices.
  • Work with Customers, Product managers, and Researchers to customize data pipelines for analysis and research.
Skills You Will Need to Be Successful
  • At least 4 years of professional, post-graduate experience collaborating on medium to large software projects.
  • Experience with one of C++, Golang, Python.
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and their data services.
  • Excellent communication and collaboration skills.
Skills That Will Differentiate Your Candidacy
  • Experience with containerization technologies (e.g., Docker, Kubernetes).
  • Experience with data governance and compliance.
  • Experience with machine learning pipelines.
  • Familiarity with robotics systems.

The base salary for this full-time position is between $147,200 - $200,900 (USD) + 15% bonus + equity + benefits. Your recruiter will share more about the specific salary range + bonus + equity for your targeted location and role during the hiring process.

At Intrinsic, we are proud to be an equal opportunity workplace. Employment at Intrinsic is based solely on a person's merit and qualifications directly related to professional competence. Intrinsic does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. It is Intrinsic's policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity.

If you have a disability or special need that requires accommodation, please contact us at: candidate-support@intrinsic.ai.

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