GCP Data Architect

Role: GCP Data Architect

Location: Leeds/Halifax, UK (Hybrid)

Employment type: Contract

Role Summary

We are seeking an experienced Cloud Data Loading Architect to design, build,

and optimise automated pipelines that ingest structured, semistructured, and

unstructured datasets into Google Cloud Platform (GCP), specifically BigQuery.

This role will lead endtoend data ingestion design—from source discovery and

schema mapping, through transformation and data quality, to scalable, secure

loads into cloudnative analytical warehouses.

The ideal candidate combines strong cloud engineering skills with handson data

integration experience and a deep understanding of BigQuery performance

optimisation.

Key Responsibilities

· Design and implement highthroughput, faulttolerant ingestion pipelines for

batch and streaming data landing in BigQuery.

· Lead data ingestion architecture patterns using Cloud Storage (GCS),

Dataflow, Dataproc, Composer (Airflow), Pub/Sub, BigQuery Storage Write

API, and related services.

· Define data loading frameworks, mapping rules, schema evolution strategy,

and metadata management.

· Create reusable ingestion blueprints that ensure governance, lineage, and

auditability.

· Establish data quality checks, validation rules, reconciliation logic, and

SLAs.

· Optimise BigQuery cost, storage, partitioning, clustering, and access

patterns.

· Collaborate with security & platform teams to ensure IAM, service

accounts, VPCSC, and encryption policies are fully applied.

· Automate CI/CD deployments for ingestion pipelines using Cloud Build,

GitHub, GitLab or Jenkins.

· Produce detailed technical documentation and coach engineering squads

in cloud ingestion standards.

· Troubleshoot ingestion failures, performance bottlenecks, and

crossplatform data integration issues.

Top 10 Skillset & Qualities (Ideal Candidate)

1. Deep Expertise in Google Cloud Data Services

BigQuery, GCS, Dataflow (Apache Beam), Pub/Sub, Dataproc, Cloud Composer,

Storage Write API.

2. Data Ingestion Engineering Mastery

Handson experience designing frameworks to load data from APIs, files,

databases, event streams, and mainframe/legacy systems into cloud stores.

3. Strong SQL & BigQuery Optimisation Skills

Partitioning, clustering, materialised views, costefficient query design, columnar

storage understanding.

4. ETL/ELT Architecture Knowledge

Experience building transformation pipelines using Airflow, Dataflow, dbt, or

equivalent orchestration tools.

5. File & Format Proficiency

Ability to work with Parquet, Avro, ORC, JSON, CSV, nested/repeated structures,

and schema evolution.

6. Strong Python and/or Java Skills

Used to build Dataflow pipelines, ingestion utilities, automation scripts.

7. Cloud Security & Governance Awareness

IAM roles, leastprivilege models, VPCSC, service accounts, artifact signing, audit

logging.

8. DevOps & CI/CD Familiarity

Cloud Build, GitHub Actions, Terraform, Cloud Deployment Manager or Pulumi.

9. Data Quality & Observability Mindset

Experience implementing validation frameworks, anomaly detection,

reconciliation rules, logging/monitoring (e.g., Cloud Logging, Cloud Monitoring).

10. Excellent Architectural Communication Skills

Ability to document, diagram, and communicate ingestion patterns to

stakeholders at technical and nontechnical levels.