GCP Data Engineer

Quick Facts

• Role: GCP Data Engineer (Senior option as Tech Lead)
• Collaboration: Direct B2B; hybrid work mode (dimension to be agreed)
• Location: Warsaw (Marynarska 12)

Description

Join a data transformation program to design, implement, and maintain data solutions on Google Cloud Platform (GCP). You will build and optimize ETL/ELT and streaming pipelines, integrate multiple sources into BigQuery and Cloud Storage, and support analytics, ML, AI, and other data-driven applications. For the Senior level, you will also lead a small data-domain micro-team as a Tech Lead.

Responsibilities

• Design, develop, and maintain data pipelines (ETL/ELT) on GCP
• Integrate data from APIs, databases, and files into BigQuery and Cloud Storage
• Design and optimize data models for data warehouses (Kimball, Data Vault, dimensional modeling)
• Implement streaming solutions using Pub/Sub, Dataflow, and Apache Beam (or Dataproc)
• Automate data-related processes using Cloud Composer (Airflow)
• Ensure data performance, quality, security, and scalability
• Collaborate with Data Analytics, Data Science, and business teams
• Create technical documentation and participate in code reviews
• Monitor and troubleshoot performance issues and optimize cloud costs
• (Senior) Lead a micro-team (2–4 people), plan work/sprints, prioritize backlog, facilitate business workshops, translate requirements into solutions and SLA/SLO

Requirements

• Minimum 2–3 years of Data Engineer experience (Senior: minimum 5 years + leading experience)
• Practical GCP experience: advanced BigQuery SQL (including optimization and cost management) and Cloud Storage
• Experience with Pub/Sub and Dataflow (Apache Beam) or Dataproc (Spark)
• Experience with Cloud Composer (Airflow) for pipeline orchestration
• Basic GCP security knowledge (IAM, KMS, DLP)
• Strong SQL knowledge (optimization, aggregations, large-scale datasets)
• Python experience (e.g., pandas, PySpark, automated tests)
• Data modeling experience (Kimball, Data Vault, dimensional modeling) and building data layers (raw/bronze, curated/silver, semantic/gold)
• Automation tools: Terraform (IaC) and CI/CD (e.g., GitLab CI, Cloud Build)
• Data quality assurance experience (testing, monitoring, alerting)
• Experience with monitoring/diagnostics tools (Cloud Monitoring, Logging)
• Technical documentation skills and participation in code review

Benefits

Not specified in the provided posting.