Senior Data Engineer

AI Futures; Berlin; Hybrid; EUR 90.000 - 110.000; Vollzeit

Zusammenfassung

AI Futures is building a global health-tech intelligence platform and seeks a Senior Data Engineer to design and operate an ontology-driven data asset. You will ingest heterogeneous clinical data from international sources, implement robust ELT pipelines, and ensure scalable, well-governed datasets.

In this role you will influence how data contracts, semantic modelling, and master data management are applied to production pipelines, collaborating with analytics and domain teams to deliver

Qualifikationen

• 5+ years of data engineering experience with ownership of a core platform.
• Experience building ELT pipelines and data contracts for reproducibility.
• Hands-on with Python and analytical SQL in cloud data environments.

Aufgaben

• Build, optimise, and operate ELT pipelines in Python/SQL.
• Drive entity resolution and master data management for international hospital data.
• Establish data contracts and schema management for reproducibility and validation.
• Optimise storage and compute costs on AWS and Snowflake.
• Implement CI/CD for data pipelines via GitHub Actions and IaC.
• Collaborate with Analytics Engineers, Data Scientists, and domain experts.

Kenntnisse

Advanced Python

Analytical SQL

Entity resolution

Ontology & semantic modelling

5+ years data engineering

CI/CD automation

AWS & Snowflake infra

Ausbildung

Bachelor's or Master's in Computer Science / Data Science / Software Engineering

Tools

Prefect

Airflow

Dagster

Splink

dedupe

recordlinkage

Pydantic

dbt contracts

JSON Schema

S3

Snowflake

Terraform

GitHub Actions

Jobbeschreibung

Global Healthcare Intelligence Platform | Germany | €100k | Permanent | Hybrid

AI Futures has been engaged by a global data and intelligence platform operating across major international markets, providing research-grade data products and benchmarking solutions to institutions, enterprises, and government bodies worldwide.

We are searching for a Senior Data Engineer within the health-tech space to support in building an intelligence platform that ingests and structures heterogeneous clinical and operational data from across international health systems into a single, queryable, and production-ready data asset.

The challenge is to build and operate a unified healthcare data ontology (consistent semantic model covering hospitals, departments, specialties, metrics, and international classification standards) turning heterogeneous multi-country hospital data into a coherent, well-governed, and highly queryable data asset.

The Role

• Build, optimise, and operate reliable ELT pipelines in Python and SQL using modern orchestrators (Prefect, Airflow, or Dagster) to ingest data from heterogeneous international sources, APIs, databases, and lakehouse storage (S3, Apache Iceberg).
• Drive entity resolution and master data management for international hospital entities - mapping raw source data to canonical structures and maintaining standardised vocabularies.
• Establish strict data contracts (Pydantic, dbt contracts) and schema management - ensuring dataset reproducibility, lineage tracking, and automated validation across all platform pipelines.
• Optimise data storage, query execution, and compute costs across AWS and Snowflake - keeping data assets secure and cost-effective at scale.
• Implement automated testing and deployment workflows for data pipelines via GitHub Actions and IaC (Terraform).
• Partner directly with Analytics Engineers, Data Scientists, and domain methodology experts to deliver documented, research-grade, and production-ready datasets.

Your Profile

• Advanced Python and analytical SQL for complex data ingestion across REST APIs, databases, and cloud lakes (S3/Iceberg).
• Hands-on Prefect, Airflow, or Dagster in production.
• Practical entity resolution and record linkage: Splink, dedupe, or recordlinkage.
• Schema management and data contracts: Pydantic, dbt contracts, or JSON Schema.
• AWS production environment depth (S3, ECS/EC2) and Snowflake.
• Automated CI/CD for data pipelines via GitHub Actions.
• 5+ years in data engineering with ownership of a core platform through build, launch, and iteration.
• Ontology and semantic modelling experience.
• Bachelor's or Master's in Computer Science, Data Science, Software Engineering, or a related quantitative field.
• Highly structured, detail-oriented, and comfortable working at the intersection of data engineering and domain complexity.

€100k Base Salary + Benefits.

Permanent | Hybrid - Berlin preferred, Hamburg okay.

AI Futures have been engaged exclusively for this search.

AI Futures | Filling the AI Skills Gap ®