BigQuery Data Engineer - Hybrid (GCP/Analytics)

Commerzbank Digital Technology Centre Poland

Łódź

Hybrid

PLN 120,000 - 180,000

Full time

4 days ago
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Benefits offered by this job

Development Plans
Life insurance
Flexible working hours
Integration events

Job summary

Commerzbank Digital Technology Centre Poland is seeking a Data Engineer to develop and optimize BigQuery datasets and ELT/ETL pipelines in a hybrid setup in Łódź. You will model data for analytics, implement data quality checks, and document lineage for curated datasets.

The role requires collaboration with business and IT stakeholders to translate requirements into technical specs, while ensuring operational stability, security, and automated testing processes.

Qualifications

  • Experience building and optimizing ELT/ETL pipelines.
  • Ability to model data for analytics and ensure data quality.
  • Collaborate with stakeholders to translate requirements into technical specs.

Responsibilities

  • Develop and optimize BigQuery datasets, views and queries (partitioning, clustering, materialized views) to meet performance and cost targets.
  • Build and maintain ELT/ETL pipelines into BigQuery (e.g., via Cloud Storage, Pub/Sub, Dataflow, Dataproc, or vendor sources), including monitoring and error handling.
  • Model data for analytics (dimensional and/or data vault concepts) and define data quality checks, lineage and documentation for curated datasets.
  • Collaborate with business and IT stakeholders to translate requirements into technical specifications, implement changes, and support testing and release activities.
  • Ensure operational stability and security (IAM, service accounts, dataset access, auditability), troubleshoot incidents, and continuously improve reliability and automation.

Skills

BigQuery
SQL
GCP Data Engineering
Python
Git CI/CD

Job description

Commerzbank Digital Technology Centre Poland is seeking a Data Engineer to develop and optimize BigQuery datasets and ELT/ETL pipelines in a hybrid setup in Łódź. You will model data for analytics, implement data quality checks, and document lineage for curated datasets.

The role requires collaboration with business and IT stakeholders to translate requirements into technical specs, while ensuring operational stability, security, and automated testing processes.

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