Staff+ Software Engineer, Databases

P-375 At Databricks, we build powerful infrastructure that accelerates innovation and enables data teams to deliver with confidence and scale. Our unified schema migration platform underpins automated, observable, and developer-friendly workflows—ensuring Databricks can continue evolving rapidly across thousands of databases and 60+ mission-critical services. What You’ll Do As a Staff Software Engineer, you’ll lead the design, development, and reliability of our global platform that manages schema and data changes at scale: Schema Migration Platform: Architecting and maintaining automated schema change infrastructure for MySQL and TiDB, while implementing versioning, rollback, validation, and auditing for safe, predictable, and fast migrations. Scale, Reliability & Test Harness: Ensuring the platform operates across thousands of global databases with zero downtime, enhancing resilience, observability, and recovery, and building a test harness for migration and deployment validation. Developer Experience & CI/CD Integration: Designing intuitive tools and APIs for seamless schema and data change management, and embedding migration workflows into CI/CD pipelines to increase velocity and reduce friction. Schema & Data management: Designing infrastructure for safe, large-scale schema and data operations like backfills and purging. This includes ensuring backfill operations are monitored, retryable, minimally disruptive, and automated to align with schema/data evolution and maintain data integrity. Your role will be crucial in: Ensuring the scalability and reliability of schema and data operations across Databricks’ global footprint. Driving predictable deployments by architecting robust test harnesses and automation. Elevating the developer experience by building accessible, resilient tools that make complex migrations feel simple. Guaranteeing the integrity of both schema and data through safe, efficient backfill strategies. What we look for: 12+

About Anthropic 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. About the role Anthropic's Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models. That includes data pipelines, some of the largest Kubernetes clusters in the world, and the databases, observability, and developer tooling that every other team at Anthropic depends on. As a Staff Software Engineer on the Infrastructure team, you'll scope and lead complex, multi-month infrastructure projects, make the architectural decisions other engineers build on, and work with research and product teams to build systems that keep pace as their needs change. Team placement happens after the interview process, based on your interests and experience alongside organizational needs. This helps us match you with the team where you'll have the most impact. Key responsibilities Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system Make architectural decisions that shape the foundation other engineers and teams build on Drive alignment on technical direction across teams, working through ambiguous problem spaces Partner with research and product teams to understand their infrastructure and compute needs, and turn them into technical designs Own the reliability, scalability, and security of the systems you build as usage and complexity grow Set technical strategy and standards for your team's infrastructure Build and improve operational processes such as incident response, postmortems, and on-call rotations, so the team learns from every incident Mentor other engineers and help raise the technical bar for the team

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The Data and Storage Services team is responsible for Affirm's data infrastructure across OLTP and OLAP systems, spanning critical online checkout databases, batch orchestration, streaming infrastructure, event-driven frameworks, BI, analytics tooling, large-scale data platforms, and agentic data tools such as semantic layers and internal platform data applications. Our mission is to provide trustworthy, intuitive, and cost-efficient solutions for Affirmers to secure, store, analyze, and transform data at exceptional scale. The Online Storage team provides a set of managed databases as a platform, used to persist data for all Affirm services. Our platform enables self-service access to OLTP storage systems, including Relational DB(MySQL), DynamoDB, Distributed SQL, Cache(Redis). As a team, we are responsible for various data and access patterns, including but not limited to mission-critical financial transactional data, data science models, and any new persistence use case. These responsibilities require us to learn and gain deep expertise in various database systems. We are looking for a highly skilled and detail-oriented Staff Software Engineer who can drive the technical roadmap for our Databases (Relational and KeyValue) identifying opportunities to improve how we build, productize, operate and improve this mission-critical infrastructure to unlock substantial value within our business. You’ll have the opportunity to directly influence your team’s roadmap in close collaboration with your peers, share your knowledge and expertise with others and learn from some of the best on our shared mission to deliver honest financial products that improve lives. What You'll Do As an integral member of the Online Storage team, You will be responsible for setting technical strategy for you

About the Role As a Staff Infrastructure Engineer on the Compute & Storage Platform team in Toast, you will design, build, and operate the foundational distributed systems powering the Toast platform as the company expands into further international markets and broadens its product offerings to encompass retail shopping. You will bridge the gap between core infrastructure and cutting-edge product development—building low-latency state and storage systems, scalable compute clusters, and high-throughput streaming pipelines. Your work will directly enable Toast product delivery across our Product Development Life Cycle (PDLC). For this role it is a requirement that you have at least 8+ years of industry experience. Key Responsibilities Online Databases and Storage: Architect, deploy, and manage low-latency, highly available storage solutions (RDS Postgres and Aurora Postgres; DynamoDB; OpenSearch; S3) to power applications across the Toast product ecosystem. High Availability & Realtime Performance: Ensure sub-second end-user latency, near-zero-downtime reliability, and high throughput across storage engines to support Toast's products across POS, phone, computer, drive-thru, and kiosk interfaces. Infrastructure for AI-Driven PDLC: Automate infrastructure provisioning and compute pipelines. Cost Optimization & Performance Engineering: Right-size compute/storage resources, implement auto-scaling policies, and manage AWS infrastructure costs without compromising platform reliability or latency SLAs. Required Qualifications 1. Core Infrastructure & Automation Cloud & Infrastructure as Code: Hands-on experience building and managing scalable cloud infrastructure on AWS using Infrastructure as Code (Terraform, CloudFormation, etc.). Software Development: Fluency in Python , Go , or a similar language for infrastructure automation, tooling, or backend development. 2. Storage & Compute Operations Databases: Deep experience operating and tuning en

P-1403 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Ingesting data into the Lakehouse is a strategic area of investment for Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is looking to solve this problem by providing ready-to-use, point-and-click connectors for a wide variety of sources, including enterprise applications (like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL Server), cloud storage, message queues, and local files. In addition to being an important part of Lakeflow and Data Engineering, Connect is also a key platform capability. Every surface in Databricks (Dashboards, Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role will need to work closely with other products to embed Connect into these surfaces. We are looking for engineers with experience in core Database internals to join our Lakeflow Connect team. A key part of Connect is to extract data from OLTP systems while imposing minimal load on production systems. To do this efficiently we are building systems that use techniques such as incremental data capture, log parsing, etc. We are looking for engineers who continue to be hands on and are looking to make a large impact on an important problem for the company. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement & optimization on large production clusters. Build architecture design, influence product roadmap, and ta

P-375 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Ingesting data into the Lakehouse is a strategic area of investment for Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is looking to solve this problem by providing ready-to-use, point-and-click connectors for a wide variety of sources, including enterprise applications (like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL Server), cloud storage, message queues, and local files. In addition to being an important part of Lakeflow and Data Engineering, Connect is also a key platform capability. Every surface in Databricks (Dashboards, Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role will need to work closely with other products to embed Connect into these surfaces. We are looking for engineers with experience in core Database internals to join our Lakeflow Connect team. A key part of Connect is to extract data from OLTP systems while imposing minimal load on production systems. To do this efficiently we are building systems that use techniques such as incremental data capture, log parsing, etc. We are looking for engineers who continue to be hands on and are looking to make a large impact on an important problem for the company. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement & optimization on large production clusters. Build architecture design, influence product roadmap, and tak