Staff Software Engineer

We are looking for a Staff Engineer - Database and Data Infrastructure to help define and drive the technical direction of database infrastructure across the company. This is a senior individual contributor role for an engineer who has designed and operated database systems at significant scale and can apply that experience to company-wide challenges.

You will work across engineering teams to shape database architecture, establish scalable patterns and platforms, anticipate future constraints, and lead initiatives that improve scalability, reliability, developer experience, and infrastructure efficiency. This is not a traditional DBA role. While deep database expertise is essential, the role is focused on architecture, platform strategy, and company-level technical impact.

Responsibilities:

• Define and evolve the long-term database and data infrastructure strategy across the company.
• Design architectures capable of supporting the next order of magnitude of growth in data volume and traffic.
• Establish architectural standards and paved roads for database selection, data modeling, partitioning, sharding, replication, consistency, availability, and data lifecycle.
• Lead complex, cross-team initiatives such as database migrations, re-platforming, sharding, multiregion architectures, and major scalability improvements.
• Identify systemic reliability, scalability, and capacity risks before they become critical production problems.
• Drive database platform capabilities that make infrastructure more self-service, observable, reliable, and easier to operate for engineering teams.
• Develop strategies for capacity planning, data growth, archival, disaster recovery, and infrastructure efficiency.
• Identify opportunities to materially improve database infrastructure cost and performance at company scale.
• Evaluate new database technologies and architectures and make pragmatic build-vs-buy and technology-selection decisions.
• Partner with senior engineers and engineering leadership on architecture and long-term technical direction.
• Mentor engineers and raise the technical bar for database and distributed-systems engineering across the organization.

Requirements:

• Significant experience as a staff engineer, principal engineer, or equivalent senior individual contributor, solving infrastructure or database problems across multiple teams.
• Deep understanding of database internals and distributed systems, including storage, indexing, partitioning, sharding, replication, consistency, transactions, availability, and failure modes.
• Experience designing and operating production database systems with multi-terabyte or larger datasets.
• Experience with high-throughput systems handling 30K-50K+ operations per second, preferably at substantially larger scale.
• Strong production experience across multiple database technologies and database architectures, including both relational and NoSQL/distributed systems.
• Experience leading major architectural changes, migrations, or scaling initiatives involving multiple engineering teams.
• Strong understanding of database reliability, capacity planning, observability, and infrastructure economics.
• Ability to take ambiguous technical problems, establish a direction, build alignment, and drive them through execution.
• Strong written and verbal communication skills with the ability to influence engineers and engineering leadership without relying on organizational authority.

Relevant Technology Experience:

• We value breadth of database architecture experience and depth of fundamentals over expertise in our specific technology stack.
• Experience in any programming language like Node.js, Java, or Python.

Experience with several technologies such as the following would be relevant:

• Relational and Distributed SQL: MySQL, PostgreSQL, Oracle, SQL Server, Amazon Aurora, Google Cloud Spanner, CockroachDB, TiDB, YugabyteDB, Vitess
• NoSQL and Distributed Databases: MongoDB, DynamoDB, Cassandra, ScyllaDB, HBase, Cosmos DB, Couchbase, Firestore.
• Search and High-Throughput Systems: Elasticsearch, OpenSearch, Redis/Valkey.
• Large-Scale Analytical Systems: ClickHouse, BigQuery, Snowflake, Redshift, Databricks, Pinot, Druid.
• You do not need experience with all of these technologies. We are looking for engineers who understand database and distributed-system fundamentals deeply enough to reason about trade-offs and make strong architectural decisions across different technologies.