GCP Data Engineer

GCP Data Engineer

Budget: up to 180zł/h

Client Description

• Global technology organization

• Delivers advanced digital solutions across:

  • data

  • infrastructure

  • analytics

• Focus on:

  • cloud transformation

  • scalability

  • engineering excellence

• Large-scale migration and modernization program

Project Description

Multi-phase cloud transformation and migration initiative:

• June 2026 → March 2027

• Executed in parallel streams

Goal

Move from:

• MVP phase

• to self-service capabilities

• and full-scale migration with automation and AI enablement

Phases

1. MVP – foundational platform setup

2. Self-service & Automation

3. Migration – large-scale migration

Responsibilities

• Design/build scalable data pipelines on GCP

• Develop and optimize data models using:

  • BigQuery

  • dbt

• Build/manage:

  • real-time processing

  • batch processing

  • Kafka pipelines

• Ensure:

  • data quality

  • consistency

  • reliability

• Support migration of legacy systems

• Collaborate with:

  • Data Architects

  • Platform Engineers

  • Analytics teams

• Enable self-service data capabilities

• Implement:

  • monitoring

  • logging

  • observability

• Optimize:

  • performance

  • cost

• Contribute to:

  • governance

  • engineering standards

Duration

• From: 08 June 2026

• To: 31 March 2027

Work Type

• Remote

Must Have

• BigQuery

• dbt

• Kafka

• Strong data pipeline experience

• SQL

• GCP/cloud data platforms

• Data modeling:

  • DWH

  • ELT/ETL

• Experience in complex environments

• Problem-solving skills

• Ownership mindset

• Communication skills

Should Have

• Data platform / data mesh concepts

• CI/CD for data workflows

• Python or Scala

• Data quality frameworks

• Governance/security best practices

• Cloud migration experience

• Airflow / Cloud Composer

Nice to Have

• Real-time analytics

• Self-service data platforms

• BigQuery cost optimization

• Enterprise transformations

• GCP certifications

• International distributed teams