Senior Data Engineer, AI & Data Platform

📋 Description

• Design, develop, and sustain the internal data warehouse and analytical data layer, integrating data from various product and operational systems into a unified and dependable source of truth.

• Establish and uphold data models, schemas, and data contracts to ensure that downstream users — including data analysts and business teams — can confidently access and utilize the data they need.

• Create and manage transformation pipelines that convert raw internal data into clean, structured analytical datasets suitable for business intelligence, reporting, and artificial intelligence applications.

• Partner with Data Analysts to facilitate AI and machine learning initiatives utilizing internal data — constructing the datasets and infrastructure required for model training and executing analytical workflows.

• Execute data quality monitoring, lineage tracking, and observability throughout the warehouse to promptly identify issues and ensure long-term data reliability.

• Collaborate with stakeholders across engineering, product, and business teams to comprehend their data requirements and translate them into scalable, well-documented data models.

• Advocate for best practices in data engineering within the team: CI/CD for data assets, testing, documentation, and reproducibility.

⛳️ Requirements

• A minimum of 10 years of hands-on experience in data engineering, showcasing ownership of production data warehouses or analytical data platforms.

• Strong command of SQL and Python.

• Extensive experience with contemporary data warehouse technologies (such as Snowflake, BigQuery, Redshift, or equivalent).

• Proficient in AWS data services (S3, Athena, Glue, or their equivalents).

• Practical experience with data transformation and modeling tools, especially dbt.

• Familiarity with workflow orchestration tools like Apache Airflow or similar.

• Experience in enabling AI workloads utilizing warehouse data.

• Solid comprehension of dimensional modeling, data vault, or other analytical data modeling methodologies.

• Knowledge of data quality tools and testing practices (such as Great Expectations, dbt tests, or similar).

• Excellent communication skills in English, both written and verbal, with the capacity to collaborate effectively with non-engineering stakeholders.

• Comfortable operating in a fully remote setting.

• Must be physically located within Europe.

🏝️ Benefits

• An opportunity to collaborate with a highly knowledgeable, high-performing, and enjoyable team.

• A diverse, dynamic, and committed international work environment.

• The flexibility to work remotely with a customizable work schedule.

• Mental health support provided by Auntie.