Senior Data Engineer Data Harmonization & BigQuery

Square One Resources REMOTE WARSAW 2026-08-12
  • Cloud & DWH: Google BigQuery, GCP
  • Orchestration: Apache Airflow (Cloud Composer)
  • Databases: BigQuery, AlloyDB / PostgreSQL, Teradata (legacy)
  • Data Integration: SQL-based ELT, SFTP, APIs (NetSuite, PSPs)
  • Governance: OpenMetadata (lineage, catalog), IAM/RBAC
  • CI/CD & DevOps: GitHub, Jenkins, Flyway, Terraform
  • Data Quality: Metadata-driven DQ framework (BigQuery + Airflow)
  • Join an international project for a global e-commerce and marketplace platform operating across multiple markets, including North America and other international regions.
  • The project focuses on harmonizing and standardizing financial and operational data coming from different regional systems and data models. The goal is to build a consistent, scalable, and high-quality data environment that will improve reporting, financial processes, and migration from legacy systems.
  • 💼 Project Details
  • Work model: 100% remote
  • Workload: Full-time
  • Equipment: Own equipment
  • Start date: ASAP
  • Recruitment process: 2 technical interviews
  • 🎯 Project Scope
  • As a Senior Data Engineer, you will be responsible for developing scalable data pipelines, data modeling and transformation in BigQuery, integrating data from multiple sources, and ensuring data quality and consistency.
  • A key part of the project will also involve process optimization, data migration from legacy systems, reconciliation, data lineage, and ensuring reliable and auditable data processing workflows.
,[Develop and maintain scalable ETL/ELT data pipelines (Bronze → Silver → Gold) using SQL and BigQuery., Ingest and integrate data from multiple sources, including SFTP, APIs, and databases., Build and optimize data models, fact and dimension tables, including SCD and surrogate key logic., Develop and support Airflow DAGs for orchestration, scheduling, and monitoring., Implement data quality checks, reconciliation, validation, and idempotent processing., Optimize BigQuery performance and costs through partitioning, clustering, and query tuning., Support CI/CD, schema evolution, data lineage, and documentation using Git, Jenkins, Flyway, and OpenMetadata., Troubleshoot pipeline issues and support data migration from legacy systems and integration with downstream systems.] Requirements: Google BigQuery, GCP, Apache Airflow, PostgreSQL, SQL, ETL/ELT Additionally: Sport subscription, Private healthcare.