Engineering Manager (Data Infrastructure)

Anthropic; New York (NY); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Comprehensive health insurance

Relocation support

Annual education stipend

Home office stipends

Commuter benefits

Equity packages

Job summary

Anthropic is seeking an Engineering Manager to lead the Data Warehouse & Streaming Infra team in New York. You will own the data platform that supports decision making, reliability, and cost governance.

You'll partner with finance, product, research and engineering to shape the roadmap, hire and grow senior engineers, and drive delivery across multi-cloud environments. This is a high-impact, high-visibility role in a fast-growing company.

Qualifications

• 3+ years of engineering management experience.
• Strong ownership of data warehouse and streaming infra.
• Experience with multi-cloud data platforms (GCP/AWS/Azure).
• Proven ability to hire, grow, and retain senior data engineers.
• Collaborate across finance, product, research and engineering to meet business needs.

Responsibilities

• Lead and scale the Data Warehouse & Streaming Infra team.
• Own end-to-end data platforms, reliability and governance.
• Define and execute roadmap for batch and streaming data infra.
• Hire senior engineers, promote high-performance culture.
• Collaborate across orgs to align with business goals.

Skills

People leadership

Hiring

Data infrastructure

Cross-team collaboration

Distributed systems

Education

Bachelor's degree or equivalent

Tools

BigQuery

Snowflake

Iceberg

Spark

dbt

Airflow

Kafka

Pub/Sub

Flink

Debezium

Job description

• Anthropic is looking for an Engineering Manager to lead and scale our Data Warehouse & Streaming Infra team. You’ll own the data platform that Anthropic runs on: the foundation every team relies on to understand the business, make decisions, and keep our systems safe. Every org is your customer
• As data volumes grow rapidly, and more of it arrives as real-time streams across multiple clouds, you’ll help your team make that stack faster, more robust, and ready for what’s next, and you’ll shape the long-term vision for how data flows through one of the fastest-growing companies ever
• This is a high-visibility, high-impact role that calls for both deep technical judgment and strong people skills. You’ll partner with leaders across finance, data science, product, engineering, and research to uncover and meet their needs, and you’ll grow a small, strong core into a large team
• Lead, grow, and mentor the Data Warehouse & Streaming Infra team, fostering a culture of ownership, collaboration, engineering excellence, and execution at speed
• Own Anthropic’s data warehousing, streaming, and processing capabilities end-to-end: “wow” user experience, ops, reliability/security/governance/cost, long-term strategic vision
• Support the team to scale and evolve our data ingestion, event streaming, change data capture, storage, orchestration, compute, query, and reporting systems at pace with business growth
• Collaborate to define and execute the roadmap for Anthropic’s batch and streaming data infrastructure, balancing immediate business needs with durable, scalable design
• Lead key platform decisions for the streaming backbone, such as managed versus self-operated Kafka, grounded in clear models of throughput, cost, and operational burden
• Partner closely across Finance, Product, Research, and Engineering to ensure data systems directly support business-critical decisions and company growth
• Drive hiring for the team — sourcing, evaluating, and closing senior data infrastructure engineers who thrive in high-growth, high-trust environments
• Establish data quality standards, freshness and delivery SLAs, and operational processes that guide engineers and users through our high-change environment
• Ensure sound infrastructure investment decisions with clear awareness of cost, capacity, reliability, and long-term maintainability tradeoffs
• Align the broader Infrastructure org on a common direction for shared platforms, tooling, and best practices across Anthropic’s data stack

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents
• Inclusive fertility benefits via Carrot Fertility
• 22 weeks of paid parental leave
• Flexible paid time off and absence policies
• Mental health support for you and your dependents
• Competitive salary and equity packages
• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
• Retirement plans with competitive matching
• Life and income protection plans
• $500/month flexible wellness and time saver stipend
• Commuter benefits
• Annual education stipend
• Home office stipends
• Relocation support for those moving for Anthropic
• Daily meals and snacks in the office

We’re looking for someone who is comfortable with ambiguity, energized by both business and technical impact, and cares deeply about people

Excel at hiring — you’ve built teams from small to large, and have sharp instincts for identifying exceptional talent

Bring deep, hands‑on expertise in both batch and streaming data infrastructure, from warehousing, pipelines, and orchestration to event streaming and change data capture, including the fundamentals of distributed log systems such as partitioning, delivery guarantees, and backpressure

Are a people-first leader who gives direct feedback, grows engineers’ careers, and builds trust with technical and non-technical partners alike, while staying steady and principled as priorities shift, knowing when to move fast and when to do it right

Have 3+ years of engineering management experience, with a track record of building and leading high-performing data infrastructure teams

Have owned systems with significant business or financial impact, and shipped at speed while improving reliability, scalability, security, and cost

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Warehouse and batch technologies such as BigQuery, Snowflake, Iceberg, Spark, dbt, or Airflow

Streaming and change data capture technologies such as Kafka, Pub/Sub, Flink, or Debezium, ideally including running them at high scale

Multi-cloud (GCP, AWS, Azure) or multi-region data platforms, including data-residency requirements

Data infrastructure at AI or ML-intensive companies: you’ve served customer teams that build pipelines for financial/billing data, model training, evaluation, or safety workflows

Building and operating observability or monitoring for data systems at scale

Working in high-growth environments where data infrastructure had to evolve rapidly to keep pace with the business