Software Engineer, Data Infrastructure

Staff+ Software Engineer, Data Infrastructure

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Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Data Infrastructure designs, operates, and scales secure, privacy-respecting systems that power data-driven decisions across Anthropic. Our mission is to provide data processing, storage, and access that are trusted, fast, and easy to use.

We're looking for infrastructure engineers who thrive working at the intersection of data systems, security, and scalability. You'll tackle diverse challenges ranging from building financial reporting pipelines to architecting access control systems to ensuring cloud storage reliability. This role offers the opportunity to work directly with data scientists, analysts, and business stakeholders while diving deep into cloud infrastructure primitives.

• Data Governance & Access Control:
  Design and implement robust access control systems ensuring only authorized users can access sensitive data. Build infrastructure for permission management, audit logging, and compliance requirements. Work on IAM policies, ACLs, and security controls that scale across thousands of users and systems.
• Financial Data Infrastructure:
  Build and maintain data pipelines and warehouses powering business-critical reporting. Ensure data integrity, accuracy, and availability for complex financial systems, including third party revenue ingestion pipelines; manage the external relationships as needed to drive upstream dependencies. Own the reliability of systems processing revenue, usage, and business metrics.
• Cloud Storage & Reliability:
  Architect disaster recovery, backup, and replication systems for petabyte-scale data. Ensure high availability and durability of data stored in cloud object storage (GCS, S3). Build systems that protect against data loss and enable rapid recovery.
• Data Platform & Tooling:
  Scale data processing infrastructure using technologies like Big Query, Big Table, Airflow, dbt, and Spark. Optimize query performance, manage costs, and enable self-service analytics across the organization.

• Have 8+ years of software engineering experience with 3+ years building data infrastructure, storage systems, or related distributed systems.
• Have deep experience with at least one of:
• Cloud data platforms (Big Query, Redshift, Snowflake) and orchestration tools (Airflow, dbt)
• Access control systems, IAM, authentication/authorization at scale
• Distributed storage systems, object storage (S3, GCS), disaster recovery
• Strong proficiency in programming languages like Python, Go, Java, or similar.
• Experience with infrastructure-as-code (Terraform, Pulumi) and cloud platforms (GCP, AWS).
• Can navigate complex technical tradeoffs between performance, cost, security, and maintainability.
• Have excellent collaboration skills – you work well with both technical and non-technical stakeholders.
• Are comfortable with ambiguity and can independently scope and drive large projects.

• Experience with security and compliance requirements (ITGC, GDPR, financial controls).
• Background in data warehousing, ETL/ELT pipelines, or analytics infrastructure.
• Experience with Kubernetes, containerization, and cloud-native architectures.
• Track record of improving data reliability, availability, or cost efficiency at scale.
• Knowledge of column-oriented databases, OLAP systems, or big data processing frameworks.
• Experience working in fintech, financial services, or highly regulated environments.
• Security engineering background with focus on data protection and access controls.

• Data:
  Big Query, Big Table, Airflow, Cloud Composer, dbt, Spark, Segment, Fivetran.
• Storage: GCS, S3.
• Infrastructure:
  Terraform, Kubernetes, GCP, AWS.
• Languages:
  
  Python, Go, SQL.