Sr Cloud Data Architect (GCP)

Sr Cloud Data Architect
Location: London, UK
Duration: Long-term contract

Senior Cloud Data Architect. The ideal candidate will have extensive experience leading large-scale data migration programs and designing automated, production-grade data pipelines across various industries. This strategic role involves deep architectural engagement with enterprise customers, driving transformation through Google Cloud's advanced data services such as Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable.

Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related technical field.
12+ years of experience in data architecture and data engineering with proven skills and leadership in large-scale cloud data programs.
8+ years of hands-on experience as a Data Engineer, with at least 3+ years specifically working with Google Cloud Platform (GCP) data services.
Strong proficiency in SQL and experience with schema design and query optimization for large datasets.
Expertise in BigQuery, including advanced SQL, partitioning, clustering, and performance tuning.
Hands-on experience with at least one of the following GCP data processing services: Dataflow (Apache Beam), Dataproc (Apache Spark/Hadoop), or Composer (Apache Airflow).
Proficiency in at least one scripting/programming language (e.g., Python, Java, Scala) for data manipulation and pipeline development.
Understanding of data warehousing and data lake concepts and best practices.
Experience with version control systems (e.g., Git).
5+ years of advanced expertise in Google Cloud data services: Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable.
Hands-on experience with orchestration tools like Apache Airflow or Cloud Composer.
Hands-on experience with one or more of the following GCP data processing services: Dataflow (Apache Beam), Dataproc (Apache Spark/Hadoop), or Composer (Apache Airflow).
Proficiency in at least one scripting/programming language (e.g., Python, Java, Scala) for data manipulation and pipeline development. Scala is mandated in some cases.
Deep understanding of data lakehouse design, event-driven architecture, and hybrid cloud data strategies.
Strong proficiency in SQL and experience with schema design and query optimization for large datasets.
Expertise in BigQuery, including advanced SQL, partitioning, clustering, and performance tuning.
Experience with version control systems (e.g., Git).
Track record of success advising C-level executives and aligning technical solutions with business goals.
Google Professional Data Engineer certification

(Mandatory).
Google Professional Cloud Architect certification or equivalent.