Data Architect
Role details
Job location
Tech stack
Job description
- Architect Scalable Data Solutions: Design and implement high-performance, secure, and scalable data architectures on Google Cloud Platform to meet business needs.
- Data Strategy & Governance: Define and enforce data architecture frameworks, standards, and best practices including data modeling, metadata management, lineage, and security.
- Solution Delivery: Lead the design, build, and deployment of cloud-based data platforms using services such as BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage.
- Data Integration & Quality: Oversee data ingestion, transformation, and curation pipelines ensuring data accuracy, consistency, and performance.
- Collaboration & Leadership: Partner with business stakeholders, product teams, and engineers to translate requirements into data-driven solutions.
- Technical Mentorship: Provide guidance and mentorship to data engineers and analysts, promoting architectural excellence and best practices.
- Performance Optimization: Continuously improve the reliability, scalability, and performance of data platforms and processes
Requirements
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Experience: 8+ years of experience in data architecture, engineering, or analytics, with at least 2 years in a Google Cloud Platform environment.
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Technical Expertise:
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Strong proficiency with Google Cloud Platform data services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud SQL, etc.)
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Hands-on experience with ETL/ELT frameworks, data warehousing, and real-time data streaming.
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Strong understanding of data modeling (3NF, Dimensional, Data Vault) and data lake / data mesh architectures.
Languages & Tools: Proficiency in SQL, Python, and tools like Terraform or Deployment Manager for infrastructure as code.
Design & Governance: Experience establishing data standards, governance frameworks, and security best practices.
Collaboration: Excellent communication skills with the ability to work across technical and business teams