Senior Data Engineer (all genders) Full-Time/Part-Time

Merck KGaA
Weiterstadt, Germany
14 days ago
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Role details

Contract type
Permanent contract
Employment type
Part-time / full-time
Experience level
Expert
Working hours
Regular working hours
Languages
English, German
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Automation of Tests Data Architecture Information Engineering Data Governance Extract Transform Load (ETL) Distributed Computing Environment Python (Programming Language) Performance Tuning SQL Databases Snowflake
+5 more
Event Driven Architecture Pyspark Information Technology Apache Kafka Data Pipelines

Job description

In your role as Senior Data Engineer (all genders), you will design, build, and operate secure, scalable data solutions for Finance using Snowflake and modern cloud-native technologies. You will translate complex financial and business requirements into robust data products and reusable services, focusing on data modeling, ingestion, transformation, and serving layers. You will collaborate with Finance stakeholders, data owners, architects, and engineers to deliver data pipelines that support financial planning, forecasting, reporting, and self-service analytics while ensuring data quality, security, governance, and observability. You will contribute to reference architectures, engineering standards, automated testing, deployment processes, and operational excellence, while helping democratize access to trusted Finance data for authorized users. Your work will advance Project Lumina and related strategic initiatives, shaping the enterprise data and AI ecosystem.

Requirements

  • University degree in Computer Science, Information Technology, Engineering, or equivalent experience.
  • Several years of professional experience in data engineering, analytics engineering, or related fields.
  • Strong hands-on Snowflake experience: data modeling, SQL, performance tuning, security, and production workloads.
  • Proven ability to design and implement cloud-based ETL/ELT data pipelines and data architectures.
  • Proficient in Python and SQL; PySpark or distributed processing experience is a plus.
  • Solid knowledge of data governance, quality, security, and lifecycle management; observability practices.
  • Experience with APIs, streaming architectures (e.g., Kafka) or event-driven patterns is advantageous.
  • Fluent English; German is a plus; ability to collaborate with both technical and non-technical stakeholders.

What we offer: We are curious minds that come from a broad range of backgrounds, perspectives, and life experiences. We believe that this variety drives excellence and innovation, strengthening our ability to lead in science and technology. We are committed to creating access and opportunities for all to develop and grow at your own pace. Join us in building a culture of inclusion and belonging that impacts millions and empowers everyone to work their magic and champion human progress!

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