Principal BigQuery Architect (Contract)
Our client is undertaking a major analytics platform modernisation, consolidating very large-scale analytical datasets into Google BigQuery and enabling native BigQuery data sharing as the primary customer access model.
We are seeking a Principal BigQuery Architect to act as the technical lead and architectural authority for the programme. The role owns the BigQuery design, access model, and performance strategy, operating at a senior, decision-making level across the delivery life cycle.
This is a lead architect role, not a hands-on ingestion or pipeline-build position.
Programme Scale & Complexity
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Total data volume: ~50 TB
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Table count: ~800 analytical tables
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Row volumes: billions of rows across time-series and reference data
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Source: Object storage (Parquet)
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Target: BigQuery analytics environment optimised for external customer access
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Access model: Replacement of IAM-heavy permissioning with BigQuery native sharing
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Use cases: High-performance analytics, customer consumption, AI-ready workloads
Candidates must have demonstrable experience designing and operating BigQuery platforms at comparable scale and complexity.
Key Responsibilities
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Own and define the end-to-end BigQuery architecture
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Set standards for:
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Analytical schema design and evolution
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Partitioning and clustering strategies at multi-TB scale
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Cost and performance optimisation for high-query workloads
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Metadata, governance, and access segmentation
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Define BigQuery-native ingestion patterns (Parquet - BigQuery)
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Design and implement BigQuery native data-sharing models, including:
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Dataset-level sharing
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Secure views
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Row- and column-level security
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Replace complex IAM-driven permissioning with scalable, managed BigQuery sharing
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Act as senior technical authority for architectural decisions, trade-offs, and risk management
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Review and approve technical designs and implementation approaches across the programme
Required Experience
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10+ years in data engineering/analytics platform roles
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5+ years hands-on BigQuery experience in production environments
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Proven experience designing large-scale BigQuery architectures (multi-TB, billions of rows)
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Strong expertise in BigQuery sharing, security, and entitlement models
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Demonstrable experience ingesting and optimising large Parquet datasets from S3/GCS
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Background working on enterprise or regulated-data platforms
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Comfortable operating as a principal-level architect within multi-team, long-running programmes
Nice to Have
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Financial-markets or time-series data experience
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Experience designing analytics platforms for external customer consumption
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Familiarity with Google Cloud best-practice architecture patterns