Senior & Mid Data Engineers with GCP

Language: English (fluent), German (nice to have)

Start date for assignment: ASAP/flexible

Duration: 6 months + extensions

Workload: Full-time

Location: 100% remote

Rate: your expectations (depending on experience), we're looking for both Mid and Senior Data Engineers!

The role focuses on enhancing data-driven personalisation for strategic digital products. The primary objective is to design and implement scalable data architectures on Google Cloud to improve user engagement, retention, and monetisation through relevant content delivery.

Main Responsibilities

• Design and implement scalable data pipelines using Google Cloud technologies (e.g., BigQuery, Dataflow, Pub/Sub).

• Develop and optimise both batch and streaming data pipelines for personalisation use cases.

• Transform and provision user and content-related data for machine learning applications.

• Implement data quality checks and establish logging and monitoring mechanisms.

• Optimise existing data processing workflows to improve performance.

• Integrate machine learning models into production workflows.

• Document data structures, transformation logic, and relevant interfaces.

• Provide technical consulting on event structures, tracking, and data architecture within the personalization framework.

Key Requirements

• Experience with Google Cloud Platform (GCP).

• Proficient in Python and FastAPI.

• Strong skills in dbt, SQL, and BigQuery.

• Familiarity with data pipeline frameworks like Airflow.

• Understanding of Kubernetes and Docker for containerization.

Nice to Have

• Experience with Vertex AI for machine learning initiatives.

• Knowledge of Terraform for infrastructure as code.

• Experience with CI/CD practices, particularly in GitLab.

• Familiarity with project tracking tools like JIRA and Confluence.

Other Details

• Team: Personalization Team in a digital product context.

• Environment: Data-driven and cloud-centric.

• Collaboration Tools: Microsoft Teams and Projektron Time Recording.