Senior Data Engineer

Title: Data Engineer/Architect

Location: Germany - Munich or Frankfurt (Preferred)

Language Requirement: German Speaker - C1 Level

This is a Hybrid role that requires the candidate to travel to Germany office periodically, ideally one or two times per month.

Need strong and Architecture level exp and GCP is mandatory.

Mandatory:

·Google Cloud Professional Data Engineer certification.

·German Speaking

·Data Architecture level

·Big Query and Ab Initio.

Scope of Work:

The successful consultant will be a key guide for customers in leveraging the Google Cloud Platform for their data needs. This involves providing expertise on the entire data lifecycle: ingestion, storage, processing, analysis, and visualization. You will be instrumental in data migration and transformation projects, designing and implementing large-scale, scalable data processing systems and pipelines. This role is focused on working with Google's strategic Cloud customers, supporting the implementation of Google Cloud products alongside the existing team.

Required Skills and Experience (5+ Years):

·Strong exp in designing, developing, and deploying high-performance data pipelines (streaming and batch).

·Proven experience building and maintaining secure, reliable, and scalable data lakes and data warehouses on Google Cloud Platform.

·Experience designing cloud enterprise solutions and leading customer projects to successful completion.

·Expertise in BigQuery and Ab Initio.

·Experience automating infrastructure provisioning, DevOps, and continuous integration/delivery (CI/CD).

·Possession of a Google Cloud Professional Data Engineer certification.

·Ability to communicate and work fluently in English.

Preferred Qualifications:

·Ability to communicate and work fluently in German.

·Experience in technical consulting.

·Advanced skills in SQL tuning and optimization for cost and performance.

·Experience building data streaming processing pipelines with an understanding of event delivery semantics.

·Experience architecting and developing production-grade, internet-scale Big Data solutions on top of public cloud managed services.

·Experience collaborating with data scientists, data analysts, and software engineers to meet complex data needs.