<p>Data is the oxygen for AI. Yet, providing <strong>secure, governed data access</strong> to AI agents, applications, and users is overly complex today. Monda's AI data platform lets anyone <strong>easily ship AI data analysts</strong> for conversational analytics and <strong>share AI-ready data to any destination</strong> without coding — powered by Snowflake's AI Data Cloud.</p> <p>Engineer the data backbone of the AI economy: We're looking for an individual contributor (IC) with proven experience in designing and building <strong>secure, high-scale data platforms</strong>. You've worked with a heterogeneous <strong>cloud data architecture</strong> supporting both structured and unstructured data sources. In addition, you have deep expertise in automated <strong>data pipeline orchestration</strong> and data observability. Preferrably, you already released <strong>AI data agents</strong> in production systems for users, creating measurable customer value.</p> <p>TL;DR: Salary range from €90-110K, work location Berlin, start date from Oct 1, 2026.</p> <h2>Tasks</h2> <p>You'll take ownership to build, architect, and innovate on our AI Data Platform:</p> <ul> <li><strong>Build</strong>: Maintain and develop our high-scale data product platform, running close to 400K data pipeline jobs per month at petabyte scale</li> <li><strong>Architect</strong>: Design and improve our cross-cloud data architecture and infrastructure to ensure high-scalability, low-latency, and cost-efficiency</li> <li><strong>Innovate</strong>: Implement AI-driven features and AI data agents that support customers in creating &#x26; exposing semantically-rich, AI-ready data products (e.g. via MCP)</li> </ul> <h2>Requirements</h2> <ul> <li><strong>Data Warehousing</strong>: In-depth experience with Snowflake (*required) and similar platforms like Databricks, BigQuery, Redshift, Azure Synapse, or ClickHouse</li> <li><strong>Data Pipeline Orchestration</strong>: Hands-on experience with Prefect (preferred) or similar tools like Airflow, Dagster, Flyte, Mage, or Metaflow</li> <li><strong>Data Ingestion &#x26; Egress</strong>: Proven experience loading/unloading data from/to S3-compatible cloud data storage like Amazon S3, GCS, Azure Blob Storage, etc.</li> <li><strong>AI Data Agents</strong>: Experience building agents, skills/CLI, and MCP servers with Snowflake Cortex AI (preferred), Google Vertex AI, Databricks, or similar</li> <li><strong>Application Engineering</strong>: Expert-level experience designing and coding data-intense back-ends with Django and Python (*required) or similar</li> <li><strong>Data Observability</strong>: Experience in montioring data quality &#x26; anomalies with tools like Metaplane, Monte Carlo, Soda, Great Expectations, or similar</li> <li><strong>Cross-Cloud Data Sharing</strong> (bonus): Experience sharing data products with Snowflake Data Sharing, Delta Sharing, BigQuery Sharing, Azure Data Share</li> </ul> <h2>Benefits</h2> <ul> <li><strong>Owners