Data Engineer (GCP)

Helvetic Payroll; Genf; Hybrid; CHF 90,000 - 130,000; Full time

Job summary

Helvetic Payroll is seeking a Data Engineer to join a 6 month contract in Geneva, hybrid setup. You will design and operate a modern cloud data platform on Google Cloud Platform, focusing on BigQuery, dbt, and CI/CD with GitLab.

You will collaborate with analytics teams to deliver scalable data products and ensure reliable, cost-efficient data pipelines. You will develop ETL/ELT pipelines, manage IaC with Terraform, and implement monitoring, security, and testing practices across the data stack.

Qualifications

• Strong experience delivering data engineering solutions on GCP, with BigQuery
• Excellent SQL skills including performance tuning and cost optimization
• Proven hands-on dbt experience, including testing and deployment
• Experience with workflow orchestration tools (Airflow/Composer or alternatives)
• Experience with GitLab CI/CD and Git workflows
• Practical Terraform for infra provisioning and management
• Solid IAM knowledge and security best practices in cloud
• Proficiency in Python for data engineering tasks
• Strong production mindset: observability, reliability, cost awareness

Responsibilities

• Design scalable data architectures on GCP using BigQuery and Cloud Composer.
• Develop and maintain ELT/ETL pipelines for reliable data workflows.
• Build analytics-ready data models using dbt across staging, warehouse and marts.
• Implement CI/CD pipelines and environment promotion in GitLab.
• Manage IaC with Terraform for cloud infra provisioning and IAM configuration.
• Develop Python components for data ingestion, orchestration, QA and automation.
• Support production operations: monitoring, alerting, incident resolution, cost optimisation.
• Collaborate with Analytics Engineers and analysts to translate requirements into data products.

Skills

BigQuery

SQL

dbt

Airflow/Composer

GitLab CI/CD

Terraform

IAM

Python

Observability

Job description

Data Engineer – GCP Data Platform

Contract duration: 6 month contract renewable
Location: Geneva / Hybrid (depending on project requirements)

As part of an ongoing enterprise data transformation program, we are looking for an experienced Data Engineer to support the design, development, and operation of a modern cloud-based data platform on Google Cloud Platform (GCP).

The consultant will collaborate closely with data, analytics, and business teams to deliver scalable and reliable data solutions that enable advanced analytics and data-driven decision making.

Mission & Responsibilities

• Design and implement scalable and robust data architectures on Google Cloud Platform, primarily leveraging BigQuery and Cloud Composer (Airflow).

• Develop and maintain ELT/ETL pipelines ensuring reliability, recoverability, and performance of data workflows.

• Build analytics-ready data models using dbt (staging, warehouse, and mart layers), including documentation, testing, and best practices.

• Implement and maintain CI/CD pipelines in GitLab, ensuring code quality, automated deployments, and environment promotion.

• Manage Infrastructure as Code (IaC) using Terraform to provision and maintain cloud infrastructure, IAM configurations, and repeatable environments.

• Develop Python components where required (data ingestion jobs, orchestration utilities, data quality checks, automation scripts).

• Support production operations, including monitoring, alerting, incident resolution, and cost/performance optimization.

• Collaborate with Analytics Engineers, Data Analysts, and business stakeholders to translate analytical requirements into scalable data products.

Technical Environment

Cloud Platform

• Google Cloud Platform (GCP): BigQuery, IAM, Composer / Airflow

Data Transformation

• dbt Core, packages/macros, testing frameworks, documentation

DevOps / CI-CD

• GitLab (merge requests, branching strategy, CI pipelines, runners, secrets management)

Infrastructure

• Terraform (modules, environment management, state management)

Development

• Python (data pipelines, APIs, automation, testing)

Required Skills

• Strong experience delivering data engineering solutions on GCP, particularly with BigQuery and related services.

• Excellent SQL skills, including performance tuning, partitioning/clustering strategies, and cost optimization.

• Proven hands-on experience with dbt, including project structuring, macros, testing, documentation, and deployment practices.

• Experience with workflow orchestration tools such as Airflow / Cloud Composer (or alternatives like Dagster or Prefect).

• Experience with GitLab CI/CD and collaborative development using Git workflows (code reviews, branching strategies, releases).

• Practical experience with Terraform for infrastructure provisioning and environment management.

• Solid understanding of IAM best practices in cloud environments (least privilege access, service accounts, group-based permissions).

• Proficiency in Python for data engineering use cases (clean code practices, testing, API integration).

• Strong production mindset, including observability, reliability, and basic security principles.

Nice to Have

• Experience with data observability tools (e.g. Monte Carlo) or custom monitoring frameworks.

• Familiarity with data ingestion platforms such as Airbyte or Fivetran.

• Experience working in modern data platform environments supporting advanced analytics or AI initiatives.