Data Platform Architect
New
A
AgileEngineData platforms
Workplace type: remote; Locations: Kraków, Olszańska St, 7, Warszawa, 00-002, Porto, 4000-000, Madrid, 28022, Poznań, 60-001, Kraków, Country code: PLPart-TimeManager
Salary not disclosed
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Job Details
- Languages
- Fluent English
- Experience
- 10+ years of experience in data architecture, solution architecture, or enterprise systems architecture.
- Required Skills
- Apache AirflowGCPBigQuerydbt
Requirements
- 10+ years of experience in data architecture, solution architecture, or enterprise systems architecture.
- Hands-on experience architecting enterprise-scale data platforms on Google Cloud Platform, including BigQuery, Dataflow, Pub/Sub, and GCS.
- Experience designing lakehouse or medallion architectures, including bronze/silver/gold layering or equivalent.
- Experience defining enterprise data governance frameworks covering data quality, lineage, metadata management, access controls, and cataloging.
- Experience advising on or leading migration of legacy ETL or data platforms to modern cloud-native architectures.
- Strong understanding of data ingestion and transformation tools such as Fivetran, dbt, and Apache Airflow/Composer.
- Experience working directly with enterprise clients as a trusted technical advisor.
- Comfort operating within a large, security-conscious enterprise and a client-controlled toolchain.
- Fluent English and ability to explain complex architecture to technical, business, and executive audiences.
- Willingness to travel occasionally for a few days at a time to the client's UK office.
Responsibilities
- Design and own the target-state lakehouse and medallion architecture for a multi-petabyte GCP data platform.
- Translate client transformation goals into scalable, secure architecture decisions and delivery roadmaps.
- Define architecture for ingestion, transformation, curation, dataset registration and cataloging, governance, and analytics-serving layers.
- Advise on migration of legacy ETL pipelines into modern GCP-native or open lakehouse patterns.
- Evaluate and help select ingestion and transformation tooling through technology proofs of concept.
- Define data governance and cataloging strategy, including metadata, lineage, and access-control design.
- Review the squad's engineering work for architectural consistency, security compliance, and maintainability.
- Present and validate architecture decisions with client executives, enterprise architecture teams, and security stakeholders.
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