Beschreibung

Need to build a scalable, reliable, cloud-native data platform?

I help fast-moving teams deliver clean, trusted data—faster.

As a Senior Data & DevOps Engineer, I bring a decade of hands-on experience designing ETL/ELT pipelines, automating deployments, and operating cloud data stacks across AWS, GCP, and Snowflake.

What I bring to the table:

→ Deep expertise in data orchestration(Airflow, Dagster, DBT, Airbyte)

→ Cloud infrastructure as code with Terraform, Kubernetes, GitLab CI/CD

→ Proven ability to cut pipeline runtimes by 60%+ and reduce costs by 40%

→ Strategic mindset: I align engineering with business goals

My typical missions include:

→ Building data platforms from scratch or refactoring legacy pipelines

→ Automating ingestion from tools like Salesforce, SAP, SharePoint, Ads

→ Designing secure, monitored, production-ready infrastructure

→ Supporting analytics, AI/ML, and BI teams with scalable workflows

I’ve delivered in sectors like retail, logistics, and infrastructure, working closely with product, data, and engineering teams.

I’m fluent in French, English, and German (A2), and based in Berlin

available for remote or hybrid projects across Europe.

Looking for a reliable data expert who delivers clean code, strong DevOps, and clear business value?

Let’s connect.

Sprachen

Französisch
Muttersprachlich oder zweisprachig
Englisch
Verhandlungssicher
Deutsch
Grundkenntnisse

Arbeitsortpräferenzen

Vor Ort möglich

Berlin (bis zu 50 km)

THE CREATIVE CLUB
DATA ENGINEER
GROSSHANDEL
Dezember 2023 - Heute (2 Jahre und 6 Monate)
Schenefeld, SH, Germany
• Developed high-performance data ingestion pipelines from S3, Salesforce, and ERP sources into Redshift/Snowflake, improving reporting latency by 40%.
• Migrated workflow orchestration from a custom TypeScript solution to Dagster, reducing job failures by 30%.
• Built CI/CD automation with GitHub Actions and Kubernetes (EKS), accelerating release cycles by 50%.
• Designed and maintained scalable batch ELT pipelines to unify procurement, sales, and marketing data in Snowflake.
• Led the transition of orchestration tools, resulting in higher job reliability and observability.
• Deployed Dagster and Airbyte on Amazon EKS for streamlined deployment and monitoring.
Kubernetes AWS SQL Amazon Redshift Snowflake
LOREAL
GCP CLOUD ENGINEER
BIOTECHNOLOGIE
Mai 2023 - September 2024 (1 Jahr und 4 Monate)
Paris, France
Co-developed an internal PaaS (BTDP) enabling 20+ teams to launch secure GCP-based data products faster.
• Built workflows for real-time data import/export using BigQuery, Firestore, and Workflows.
• Integrated budget-tracking and access control systems via Pub/Sub, IAM, and Azure AD, reducing compliance overhead.
• Enabled Data Governance to a Data Mesh data platform by enforcing attribute-based rules across GCP services such as BigQuery and Cloud Storage.
• Automated temporary access provisioning for sensitive resources like BigQuery and Cloud Storage.
• Optimized service account and app permission management using Firestore and Azure MS Graph.
Google Cloud Platform (GCP) BigQuery Python FastAPI Microsoft Azure
EUROPOL
ELASTICSEARCH CONSULTANT
ÖFFENTLICHER SEKTOR & KÖRPERSCHAFTEN
November 2022 - April 2023 (5 Monate)
The Hague, ZH, Netherlands
• Designed a real-time observability platform for ingesting logs from 20+ applications into Elasticsearch, improving threat detection.
• Led ELK migration (v7.17 to v8.9), cutting query response time by 30%.
• Built dashboards and alerting systems in Kibana for Europol teams.
• Integrated Logstash pipelines and AM Queues to streamline multi-source ingestion.
• Deployed and configured Elasticsearch Data Streams for scalable data storage.
• Managed infrastructure with Puppet and Kubernetes for consistent deployment.
Elastic Stack (ELK) Elasticsearch Kibana Kubernetes Logstash