Build and operate data pipelines that move event streams, document metadata, and usage data into our cloud data warehouse (ClickHouse Cloud, Snowflake, Azure)
Design and maintain APIs for analytics and event extraction, with multi-tenant security baked in (RBAC, OAuth, SSO/SAML)
Make data usable: whether that's modeling schemas for BI consumers, investigating a data quality issue, or helping a stakeholder understand what's possible with the data we have
Keep things reliable and secure through automated tests, monitoring, and handling of sensitive data within SOC 2 and ISO 27001 environments
Power our AI experiences by working with vector stores, indexing, and retrieval systems
Drive engineering best practices across the platform: CI/CD, peer reviews, infrastructure as code, API versioning, and clear documentation

A track record of building data platforms in SaaS or cloud-native analytics environments
Strong programming skills, with depth in at least one of Python or Kotlin and willingness to work across both
Hands-on experience with MPP/cloud data warehouses (e.g., ClickHouse, Redshift, BigQuery, Snowflake, Azure Synapse) and cloud infrastructure on AWS or Azure
Practical experience designing, consuming, and maintaining APIs
Familiarity with multi-tenant security patterns: RBAC, row-level security, and identity standards such as OAuth and SAML/SSO
Solid engineering fundamentals: CI/CD, automated testing, observability, and infrastructure as code (Terraform a plus)
Working knowledge of data privacy requirements (PII handling, GDPR) and experience operating within compliance frameworks like SOC 2 or ISO 27001
Experience integrating with BI tools (Power BI, Tableau, Looker)
Familiarity with semantic search, embeddings, or vector stores (e.g., Pinecone, pgvector)
Exposure to event-driven or streaming architectures (Kafka, Kinesis, SQS/SNS)
Experience with containerisation (Docker, ECS/Fargate)
Interest in leveraging LLMs and AI tooling to accelerate data engineering work

Senior Data Engineer

Key skills