Senior Data Engineer

This is a fully remote position, open to applicants in Netherlands.

📋 Description

• Develop and manage data pipelines that transport event streams, document metadata, and usage data into our cloud data warehouse (ClickHouse Cloud, Snowflake, Azure).

• Create and sustain APIs for analytics and event extraction, incorporating multi-tenant security features (RBAC, OAuth, SSO/SAML).

• Enhance data usability by modeling schemas for BI consumers, investigating data quality issues, or assisting stakeholders in understanding the potential of the available data.

• Ensure reliability and security through automated testing, monitoring, and the management of sensitive data in accordance with SOC 2 and ISO 27001 standards.

• Support our AI initiatives by collaborating with vector stores, indexing, and retrieval systems.

• Promote engineering best practices across the platform, including CI/CD, peer reviews, infrastructure as code, API versioning, and comprehensive documentation.

⛳️ Requirements

• Proven experience in building data platforms within SaaS or cloud-native analytics environments.

• Proficient programming skills, particularly in at least one of Python or Kotlin, with a willingness to work in both languages.

• Practical experience with MPP/cloud data warehouses (e.g., ClickHouse, Redshift, BigQuery, Snowflake, Azure Synapse) and cloud infrastructure on AWS or Azure.

• Hands-on experience in designing, consuming, and maintaining APIs.

• Understanding of multi-tenant security patterns: RBAC, row-level security, and identity standards such as OAuth and SAML/SSO.

• Strong engineering fundamentals including CI/CD, automated testing, observability, and infrastructure as code (experience with Terraform is a plus).

• Knowledge of data privacy requirements (such as PII handling and GDPR) and experience working within compliance frameworks like SOC 2 or ISO 27001.

• Experience integrating with BI tools (e.g., Power BI, Tableau, Looker).

• Familiarity with semantic search, embeddings, or vector stores (such as Pinecone, pgvector).

• Exposure to event-driven or streaming architectures (e.g., Kafka, Kinesis, SQS/SNS).

• Experience with containerization technologies (e.g., Docker, ECS/Fargate).

• Interest in leveraging LLMs and AI tools to enhance data engineering processes.

🏝️ Benefits

• Competitive compensation.

• Exceptional career development opportunities.

• Remote-first, globally distributed team events throughout the year.