Responsibilities
- designing, building and maintaining data models (mainly in dbt/Dataform) on top of BigQuery
- developing and optimizing analytical datasets and data marts for business consumption
- collaborating with data engineers and business stakeholders to translate requirements into scalable data solutions
- implementing data transformation logic and ensure data quality, testing, and validation
- supporting migration of existing pipelines from AWS / Snowflake / Azure into GCP
- working with ingestion pipelines (Pub/Sub, Datastream, Dataflow) and ensure alignment with downstream reporting needs
- contributing to governance, data cataloging, and lineage (Knowledge Catalog)
- enabling self-service analytics through reusable models, templates, and standards
- validating data consistency during migration and support cutover (parity vs legacy systems)
- supporting BI layer (e.g. QuickSight) and ensure consistency of KPIs across domains
- participating in establishing best practices for analytics engineering and data product development
Work Arrangement
Remote (Country) — CEE region
You will be:
- designing, building and maintaining data models (mainly in dbt/Dataform) on top of BigQuery
- developing and optimizing analytical datasets and data marts for business consumption
- collaborating with data engineers and business stakeholders to translate requirements into scalable data solutions
- implementing data transformation logic and ensure data quality, testing, and validation
- supporting migration of existing pipelines from AWS / Snowflake / Azure into GCP
- working with ingestion pipelines (Pub/Sub, Datastream, Dataflow) and ensure alignment with downstream reporting needs
- contributing to governance, data cataloging, and lineage (Knowledge Catalog)
- enabling self-service analytics through reusable models, templates, and standards
- validating data consistency during migration and support cutover (parity vs legacy systems)
- supporting BI layer (e.g. QuickSight) and ensure consistency of KPIs across domains
- participating in establishing best practices for analytics engineering and data product development
Your profile:
- strong experience as Analytics Engineer / Data Engineer with focus on analytics layer
- hands-on experience with dbt (or Dataform) and SQL-based transformations
- experience with GCP stack (BigQuery, Cloud Storage, Composer/Airflow)
- strong SQL skills and experience building data models (dimensional modeling, data marts)
- experience working with modern data platforms / lakehouse architectures
- understanding of data pipelines, ETL/ELT processes, and orchestration (Airflow/Dagster or similar)
- experience with data validation, testing, and data quality frameworks
- ability to work with stakeholders and translate business needs into data models
- familiarity with data migration projects (replatforming, consolidation)
- experience with CI/CD for data (e.g., Terraform, GitHub Actions, Cloud Build)
- knowledge of data governance, cataloging and lineage tools
- exposure to streaming or near real-time data processing
- familiarity with AI/ML or analytics enablement use cases
- practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery
Nice to have:
- experience with Knowledge Catalog / data catalog tools
- Experience with BI tools (e.g., QuickSight or similar)
- exposure to self-service data platforms
- understanding of FinOps / cost optimization in cloud data platforms
- experience in highly distributed enterprise environments
Recruitment Process
- CV review
- HR call
- Technical Interview
- Client Interview
- Decision
