Sr Cloud Data Architect
Posted 1 week ago by W3Global on Linkedin
Job Description: The Sr Cloud Data Architect role involves providing technical leadership for enterprise-scale data migration and modernization initiatives, focusing on architecting end-to-end data platforms using various Google Cloud services. The position requires mentoring engineering teams and acting as a trusted advisor to stakeholders across multiple industries. The role emphasizes driving data quality, governance, and security standards while participating in technical workshops and architecture reviews. A strong background in data architecture and engineering, particularly with Google Cloud services, is essential for success in this position.
Key Responsibilities:
- Provide technical leadership and strategic direction for enterprise-scale data migration and modernization initiatives.
- Architect end-to-end data platforms using Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable.
- Define and implement real-time and batch processing pipelines for complex use cases involving streaming analytics, ML feature engineering, and automation.
- Act as a trusted advisor to senior technical and business stakeholders across industries (e.g., telecom, retail, financial services).
- Drive data quality, governance, lineage, and security standards across enterprise data pipelines.
- Mentor engineering teams and lead best practice adoption across data architecture, orchestration, and DevOps tooling.
- Participate in technical workshops, executive briefings, and architecture reviews to evangelize GCP data capabilities.
Skills Required:
- 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.
- 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.
- 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.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: on-site
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Location: United Kingdom (Work from Office - Onsite Presence is required)
Key Responsibilities
- Provide technical leadership and strategic direction for enterprise-scale data migration and modernization initiatives.
- Architect end-to-end data platforms using Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable.
- Define and implement real-time and batch processing pipelines for complex use cases involving streaming analytics, ML feature engineering, and automation.
- Act as a trusted advisor to senior technical and business stakeholders across industries (e.g., telecom, retail, financial services).
- Drive data quality, governance, lineage, and security standards across enterprise data pipelines.
- Mentor engineering teams and lead best practice adoption across data architecture, orchestration, and DevOps tooling.
- Participate in technical workshops, executive briefings, and architecture reviews to evangelize GCP data capabilities.
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.
- 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.
Preferred Qualifications
- Experience with modernization of on-premise and mainframe data environments into cloud-native architectures.
- Knowledge of regulatory data requirements across financial, healthcare, and telecom sectors.
- Familiarity with IaC (Terraform), GitOps, and CI/CD for data pipeline deployment.
- Strong communication, stakeholder management, and mentoring skills.
Negotiable
London, England, United Kingdom
Undetermined
Onsite
IT
Not Specified
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Job Description: The Sr Cloud Data Architect role involves providing technical leadership for enterprise-scale data migration and modernization initiatives, focusing on architecting end-to-end data platforms using various Google Cloud services. The position requires mentoring engineering teams and acting as a trusted advisor to stakeholders across multiple industries. The role emphasizes driving data quality, governance, and security standards while participating in technical workshops and architecture reviews. A strong background in data architecture and engineering, particularly with Google Cloud services, is essential for success in this position.
Key Responsibilities:
- Provide technical leadership and strategic direction for enterprise-scale data migration and modernization initiatives.
- Architect end-to-end data platforms using Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable.
- Define and implement real-time and batch processing pipelines for complex use cases involving streaming analytics, ML feature engineering, and automation.
- Act as a trusted advisor to senior technical and business stakeholders across industries (e.g., telecom, retail, financial services).
- Drive data quality, governance, lineage, and security standards across enterprise data pipelines.
- Mentor engineering teams and lead best practice adoption across data architecture, orchestration, and DevOps tooling.
- Participate in technical workshops, executive briefings, and architecture reviews to evangelize GCP data capabilities.
Skills Required:
- 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.
- 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.
- 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.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: on-site
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Location: United Kingdom (Work from Office - Onsite Presence is required)
Key Responsibilities
- Provide technical leadership and strategic direction for enterprise-scale data migration and modernization initiatives.
- Architect end-to-end data platforms using Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable.
- Define and implement real-time and batch processing pipelines for complex use cases involving streaming analytics, ML feature engineering, and automation.
- Act as a trusted advisor to senior technical and business stakeholders across industries (e.g., telecom, retail, financial services).
- Drive data quality, governance, lineage, and security standards across enterprise data pipelines.
- Mentor engineering teams and lead best practice adoption across data architecture, orchestration, and DevOps tooling.
- Participate in technical workshops, executive briefings, and architecture reviews to evangelize GCP data capabilities.
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.
- 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.
Preferred Qualifications
- Experience with modernization of on-premise and mainframe data environments into cloud-native architectures.
- Knowledge of regulatory data requirements across financial, healthcare, and telecom sectors.
- Familiarity with IaC (Terraform), GitOps, and CI/CD for data pipeline deployment.
- Strong communication, stakeholder management, and mentoring skills.
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