Anchor: Anthropic · Staff+ Software Engineer, Data Infrastructure · fetched 2026-11-04.
One posting per company, chosen by title similarity + technique overlap. Not a category report.
Snapshot
Technique matrix
The roles in depth
Anthropic — Staff+ Software Engineer, Data Infrastructure
- Level: staff+ · Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY · Days open: 264
- Experience stated: 10+ years, 3+ years
- Apply: https://job-boards.greenhouse.io/anthropic/jobs/5114768008
- Crawl / index / data pipeline: "users and systems. Financial Data Infrastructure: Build and maintain data pipelines and warehouses powering business-critical reporting. Ensure data integrity, accuracy, and availability for co"
- Distributed systems: "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 stora"
- Infrastructure as code (Terraform / Pulumi): "ogramming 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 performan"
- Kubernetes / cloud infra: "cientists, analysts, and business stakeholders while diving deep into cloud infrastructure primitives. Responsibilities: Within Data Infra, you may be matched to critical business areas including: Dat"
- Spark / Flink / Kafka / Ray: "processing infrastructure using technologies like BigQuery, BigTable, Airflow, dbt, and Spark. Optimize query performance, manage costs, and enable self-service analytics across the organ"
OpenAI — Software Engineer, Data Infrastructure
- Level: mid/unspecified · Location: San Francisco · Days open: 860
- Experience stated: 4+ years, 4+ years
- Apply: https://jobs.ashbyhq.com/openai/f763c6b3-5167-4a67-b691-4c3fa2c44156
- Distributed systems: "tructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco,"
- Latency / serving / caching: "g and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineerin"
- Infrastructure as code (Terraform / Pulumi): "eberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure prob"
- Kubernetes / cloud infra: "eberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure prob"
- Spark / Flink / Kafka / Ray: "ct, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a v"
Databricks — Staff Software Engineer - Data Platform
- Level: staff+ · Location: Bengaluru, India · Days open: 807
- Experience stated: 10+ years, 4+ years
- Apply: https://databricks.com/company/careers/open-positions/job?gh_jid=7601572002
- Crawl / index / data pipeline: "rm vision and requirements for the Databricks product. Build reliable data pipelines and solve data problems using Databricks, our partner’s products, and other OSS tools. Provide early feedback"
- Distributed systems: ". 10+ years of industry experience building and operating large-scale distributed systems. 4+ years of experience providing technical leadership on planet-scale production data systems Experience lea"
- Latency / serving / caching: "leading architecture efforts for performance-sensitive systems (e.g., latency-critical services, multi-tenant platforms, large-scale indexing pipelines). Strong communication skills and t"
- Infrastructure as code (Terraform / Pulumi): "CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling. Partner with our engineering teams to provide leadership in developing the long-term vision and requ"
- Spark / Flink / Kafka / Ray: "ified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At"
Differences that matter
- The matrix above is literal: a ✅ means the description names the technique family.
- Day counts are first-publication age; older postings may be evergreen requisitions.
- Compensation is omitted unless a posting states a range.
Rehearse this
- Cache/backpressure/partial failure:
/questions/cache-warmup-backpressure - Systems and storage drills:
/question-bank - Performance practice:
/python