Senior Data Engineer (GCP) | BigQuery & Data Pipelines

Experis; Polska; Hybrid; PLN 200,000 - 340,000; Full time

Benefits offered by this job

Medical package

Sport subsidy

Lunch subsidy

Life insurance

Job summary

Experis seeks a Senior Data Engineer GCP to join a data-centric team in Poland. You will build data pipelines in dbt and orchestrate workloads with Airflow/Cloud Composer, developing Python and PySpark components, and shaping the Gold/Platinum medallion layers in BigQuery.

You will optimize BigQuery costs, implement robust CI/CD with GitHub Actions, manage Terraform, and uphold data security (IAM, RBAC/ABAC, DLP) while contributing to Data Governance and data lineage across a Hub & Spoke model.

Qualifications

• 5+ years in Data Engineering with hands-on GCP experience.
• Proficient with BigQuery data modeling, partitioning, clustering, and cost optimization.
• Hands-on with dbt, Airflow/Cloud Composer, Python and PySpark.
• Strong SQL skills and experience with Terraform.
• CI/CD using GitHub Actions and monitoring pipelines.

Responsibilities

• Build and maintain data pipelines using dbt and Airflow/Cloud Composer.
• Develop data processing components in Python and PySpark.
• Design the Gold/Platinum medallion layers of the BigQuery data lake.
• Optimize BigQuery performance and costs via partitioning and clustering.
• Build CI/CD pipelines with GitHub Actions and IaC with Terraform.
• Implement data security models: IAM, policy tags, DLP.
• Contribute to Data Governance, including Dataplex, metadata, and lineage.
• Conduct code reviews and define engineering standards.
• Provide technical guidance within Hub & Spoke model on GCP.

Skills

BigQuery

dbt

Apache Airflow

Python

PySpark

SQL

Terraform

GitHub Actions

Data security on GCP

IAM / RBAC / ABAC

Education

Google Professional Data Engineer certification

Tools

Cloud Composer

Dataproc

Pub/Sub

Job description

Experis seeks a Senior Data Engineer GCP to join a data-centric team in Poland. You will build data pipelines in dbt and orchestrate workloads with Airflow/Cloud Composer, developing Python and PySpark components, and shaping the Gold/Platinum medallion layers in BigQuery.

You will optimize BigQuery costs, implement robust CI/CD with GitHub Actions, manage Terraform, and uphold data security (IAM, RBAC/ABAC, DLP) while contributing to Data Governance and data lineage across a Hub & Spoke model.