Albert's mission is to help chemists change the world. We build Albert OS, the first AI-native operating system for materials science, helping enterprise R&D teams capture their scientific knowledge, run smarter experiments, and bring better materials to market faster. Our data systems are at the heart of that mission
We're looking for a Staff Software Engineer, Data to lead the design and evolution of the data infrastructure that powers Albert OS. This is a high-impact role for someone who thinks deeply about data architecture across analytical and transactional systems, cares about correctness and reliability at scale, and can influence engineering direction across teams.
Responsibilities- Own the architecture and evolution of our core data platforms, spanning Lakehouse infrastructure, analytical pipelines, and transactional systems.
- Design and build scalable data ingestion and transformation pipelines (batch and streaming) with a strong emphasis on data quality, reliability, and downstream usability.
- Define data modeling standards across our stack, including dimensional, medallion, and schema-first patterns.
- Drive performance optimization across SQL and NoSQL systems, with a focus on query efficiency, partitioning strategies, and throughput at scale.
- Collaborate closely with API and Data Science teams to build robust pipelines and shared data contracts.
- Establish and enforce data security practices, including encryption boundaries, access controls, and tenant isolation.
- Set standards for observability across data systems using tools like Grafana, CloudWatch, and OpenTelemetry.
- Mentor engineers across the org and lead architectural decisions through review and documentation.
- 8+ years of experience in data engineering or a closely related discipline, with a focus on large-scale distributed systems.
- Hands-on experience with Databricks and lakehouse architecture patterns.
- Strong understanding of OLAP systems and experience designing star schema and galaxy schema data models.
- Strong understanding of transactional systems design, including consistency models, write patterns, and operational reliability.
- Expertise in data modeling across both SQL and NoSQL ecosystems.
- Strong programming skills in Python and Spark with an emphasis on clean, maintainable code.
- Hands-on experience with AWS services including S3, Lambda, and IAM.
- Familiarity with observability stacks (Grafana, CloudWatch) and experience debugging production bottlenecks.
- Knowledge of DynamoDB and PostgreSQL is a plus.
- Excellent communication skills and a track record of influencing cross-functional technical decisions.
- Builder Mindset: Wants to create foundational systems that others build on.
- Curiosity: Genuine interest in how your work enables scientific discovery.
- Rigor: Commitment to quality. AI makes mistakes confidently, and our customers won't accept hand-waving.
- Collaboration: Partners effectively with engineers across Product Engineering, AI/ML, and Enterprise Engineering.
- Adaptability: Comfortable in a dynamic, fast-moving environment where priorities shift.
- Revenue from day one. The product is loved and used by thousands of users.
- Small team. Flexible hours. Collaboration over process.
- No micro-management. You'll own your work.
- Building software for a sustainable future.
Skills Required
- 8+ years of experience in data engineering or a closely related discipline focused on large-scale distributed systems
- Hands-on experience with Databricks and lakehouse architecture patterns
- Strong understanding of OLAP systems and experience designing star schema and galaxy schema data models
- Strong understanding of transactional systems design, including consistency models, write patterns, and operational reliability
- Expertise in data modeling across SQL and NoSQL ecosystems
- Strong programming skills in Python and Spark
- Hands-on experience with AWS services including S3, Lambda, and IAM
- Familiarity with observability stacks such as Grafana and CloudWatch, and experience debugging production bottlenecks
- Knowledge of DynamoDB and PostgreSQL
- Excellent communication skills and a track record of influencing cross-functional technical decisions
What We Do
Meet Albert, the partner for the scientist of the future. Enterprises partner with Albert to reimagine how they invent. From digitalizing R&D and managing change at scale, to unlocking entirely new business models with AI, chemical and materials science leaders rely on Albert to achieve digital transformation — and ensure it delivers lasting value. Every day, scientists in 30+ countries use Albert to accelerate R&D with AI trained like a chemist, bringing better products to market, faster. Your science moves the world forward. We move everything else out of your way.
