Principal Data Architect

Essential Responsibilities:

• Architecture & Design

• Define and document the overall data platform architecture in GCP, including ingestion (Pub/Sub, Dataflow), storage (BigQuery, Cloud Storage), and orchestration (Composer, Workflows).
• Establish data modeling standards (star/snowflake schemas, partitioning, clustering) to optimize performance and cost.

• Platform Implementation

• Build scalable, automated ETL/ELT pipelines for IoT telemetry and events.
• Implement streaming analytics and CDC where required to support real-time dashboards and alerts.

• Data Products & Exchange

• Collaborate with data scientists and product managers to package curated datasets and ML feature tables as consumable data products.
• Architect and enforce a secure, governed data exchange layerleveraging BigQuery Authorized Views, Data Catalog, and IAMto monetize data externally.

• Cost Management & Optimization

• Design cost-control measures: table partitioning/clustering, query cost monitoring, budget alerts, and committed-use discounts.
• Continuously analyze query performance and storage utilization to drive down TCO.

• Governance & Security

• Define and enforce data governance policies (cataloging, lineage, access controls) using Cloud Data Catalog and Cloud IAM.
• Ensure compliance with privacy, security, and regulatory requirements for internal and external data sharing.

• Stakeholder Enablement

• Partner with business stakeholders to understand data needs and translate them into platform capabilities and SLAs.
• Provide documentation, training, and self-service tooling (Data Studio templates, APIs, notebooks) to democratize data access.

• Mentorship & Leadership

• Coach and mentor engineers on big data best practices, SQL optimization, and cloud-native architecture patterns.
• Lead architecture reviews, proof-of-concepts, and pilot projects to evaluate emerging technologies (e.g., BigQuery Omni, Vertex AI).

What You'll Bring to Our Team

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 8+ years designing and operating large-scale data platforms, with at least 5 years hands-on experience in GCP (BigQuery, Dataflow, Pub/Sub).
• Deep expertise in BigQuery performance tuning, data partitioning/clustering, and cost-control techniques.
• Proven track record building streaming and batch pipelines (Apache Beam, Dataflow, Spark).
• Strong SQL skills and experience with data modeling for analytics.
• Familiarity with data governance tools: Data Catalog, IAM, VPC Service Controls.
• Experience with Python or Java for ETL/ELT development.
• Excellent communication skills, able to translate technical solutions for non-technical stakeholders.