Data Architect GCP @ SquareOne

2 days ago

Remote Warsaw, Czech Republic SquareOne Full time
  • 7+ years of experience in data architecture, database design, and data engineering
  • Proven expertise in Google Cloud Platform (GCP), including: Dataplex, BigQuery, Dataflow (Apache Beam) and other GCP-native tools
  • Strong experience with Apache-based data pipelining tools (Beam, Airflow, Kafka, Spark)
  • Expertise in data modeling (conceptual, logical, physical) for structured and semi-structured data
  • Solid knowledge of ETL/ELT processes, data transformation, and cloud integration techniques
  • Strong understanding of data governance, metadata management, and security compliance within GCP
  • Excellent communication and presentation skills — ability to engage with clients and translate complex data concepts into actionable business insights
  • Proven ability to collaborate with cross-functional teams (engineers, analysts, business stakeholders) to ensure data integrity and accessibility

As a Data Architect, you will play a key role in designing and implementing scalable, cloud-native data solutions on Google Cloud Platform (GCP). You’ll partner with engineering, analytics, and business teams to build reliable data architectures that support enterprise-scale analytics and compliance.

,[Designing, implementing, and optimizing cloud-native data architectures within GCP, Leveraging Dataplex for data governance, cataloging, and lifecycle management, Building and managing Apache-based data pipelines (Beam, Airflow, Kafka, Spark) to ensure efficient, scalable data processing, Developing and maintaining ETL/ELT workflows, focusing on both cloud-based and streaming architectures, Defining and enforcing data governance and compliance best practices across platforms, Collaborating with engineering and analytics teams to ensure data availability, reliability, and performance, Providing expertise in big data processing and enterprise-scale analytics solutions on GCP, Staying current with emerging data technologies and recommending improvements to existing architectures] Requirements: GCP, Google Cloud Platform, Data pipelines, Airflow, Kafka, Spark, ETL, Big Data, Data engineering, BigQuery, Apache Beam, Data modeling, Cloud, Security

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