Staff Software Engineer - AI Data Platform & Snowflake , Berlin)

Monda Labs
Berlin, Germany
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
€90,000.0 - €110,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Airflow Amazon S3 ARM Architecture BigQuery Cloud Database Cloud Storage Data Infrastructure Data Sharing Data Warehousing Django Web Framework Python (Programming Language)
+12 more
DataOps Data Ingestion Azure Data Factory Snowflake Low Latency Data Management Vertica Network Server Azure Synapse Analytics Data Pipelines Amazon Redshift Databricks

Job description

Engineer the data backbone of the AI economy: We’re looking for an individual contributor (IC) with proven experience in designing and building secure, high-scale data platforms. You’ve worked with a heterogeneous cloud data architecture supporting both structured and unstructured data sources. In addition, you have deep expertise in automated data pipeline orchestration and data observability. Preferrably, you already released AI data agents in production systems for users, creating measurable customer value., You’ll take ownership to build, architect, and innovate on our AI Data Platform:

  • Build: Maintain and develop our high-scale data product platform, running close to 400K data pipeline jobs per month at petabyte scale
  • Architect: Design and improve our cross-cloud data architecture and infrastructure to ensure high-scalability, low-latency, and cost-efficiency
  • Innovate: Implement AI-driven features and AI data agents that support customers in creating & exposing semantically-rich, AI-ready data products (e.g. via MCP)

Requirements

  • Data Warehousing: In-depth experience with Snowflake (*required) and similar platforms like Databricks, BigQuery, Redshift, Azure Synapse, or ClickHouse
  • Data Pipeline Orchestration: Hands-on experience with Prefect (preferred) or similar tools like Airflow, Dagster, Flyte, Mage, or Metaflow
  • Data Ingestion & Egress: Proven experience loading/unloading data from/to S3-compatible cloud data storage like Amazon S3, GCS, Azure Blob Storage, etc.
  • AI Data Agents: Experience building agents, skills/CLI, and MCP servers with Snowflake Cortex AI (preferred), Google Vertex AI, Databricks, or similar
  • Application Engineering: Expert-level experience designing and coding data-intense back-ends with Django and Python (*required) or similar
  • Data Observability: Experience in montioring data quality & anomalies with tools like Metaplane, Monte Carlo, Soda, Great Expectations, or similar
  • Cross-Cloud Data Sharing (bonus): Experience sharing data products with Snowflake Data Sharing, Delta Sharing, BigQuery Sharing, Azure Data Share

Benefits & conditions

  • Ownership: Participation in our employee stock options program (VESOP)
  • Balance: 30 days of vacation and flexible working hours (aligned with team)
  • Mobility: €63 monthly public transport budget (covers your Deutschland-Ticket)
  • Flexibility: 3 days office / 2 days home office (options for remote work periods)
  • Hardware: High-end hardware of your choice (Mac/Linux)

We’re looking forward to receiving your application and encourage to apply from any background and even if you don’t fulfill all requirements.

We commit to answer fast to your application. The process will be led by our tech founder personally and you will get the chance to speak with our engineering team about your code and our platform.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

2:00 min

Separating dataset creation from low-level software implementation steps

Jan Zawadzki · World Congress 2022

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

3:05 min

Audience questions on AI agents and pipeline vectorization

Joy Joy · World Congress 2024

3:14 min

Structuring career paths and localized data architectures

Ulrich Wurstbauer +1 · LIVE

2:35 min

Evaluating when to adopt Argo Workflows for data pipelines

Hauke Brammer · World Congress 2023

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