Senior Data Architect

Anson McCade
London, England
13 months ago
Applications closed

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The Opportunity
A leading global consultancy organisation is seeking a skilled Data Architect to design and deliver robust, scalable data platforms on Google Cloud Platform (GCP). The ideal candidate will bring extensive experience in building and maintaining large-scale data warehouses, ensuring high standards of data quality, and adhering to best practices in data architecture.

In order to make an application, simply read through the following job description and make sure to attach relevant documents.

Key Responsibilities
Define and develop the overall data strategy in line with client requirements and compliance standards.
Lead and mentor a team of data engineers to implement scalable and efficient data solutions.
Translate business needs into technical solutions by collaborating with both technical and non-technical stakeholders.
Ensure the design and deployment of data platforms follow GCP best practices for performance, reliability, and security.

Required Skills and Experience
Proven background in designing data warehouse and data lake architectures.
Demonstrable experience in building and operating large-scale data platforms on Google Cloud Platform, with a focus on data quality at scale.
Hands-on expertise in core GCP data services such as BigQuery, Composer, Dataform, Dataproc, and Pub/Sub.
Strong programming skills in PySpark, Python, and SQL.
Proficiency in ETL processes, data mining, and data storage principles.
Experience with BI and data visualisation tools, such as Looker or Power BI.
Excellent communication skills, with the ability to effectively bridge technical and business discussions.

Desirable Qualifications and Experience
Degree (BSc, MSc, or PhD) in Computer Science, Mathematics, or a related field.
Familiarity with alternative cloud and data platforms such as Databricks, Snowflake, Azure, or AWS.
Knowledge of DevOps/DataOps methodologies and experience with CI/CD pipelines.
Understanding of monitoring, logging, and troubleshooting in cloud-based environments.
Google Cloud Professional Data Engine er

certification (or equivalent) is highly advantageous.

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Where to Advertise Data Science Jobs in the UK (2026 Guide)

Where to advertise data science jobs UK in 2026: the specialist boards, communities and channels that actually reach senior and lead data science talent. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.