Data Architect, Google Cloud Platform (GCP)
Data Architect, Google Cloud Platform (GCP)
Posted 2 days ago
SENIORITY
Lead
About the role
- Client Delivery
- Architect scalable, secure, and high-performing data platforms on GCP, with BigQuery as a core analytics and data warehousing technology.
- Lead technical design across data ingestion, transformation, storage, modeling, governance, orchestration, and consumption.
- Design BigQuery data models, optimization strategies, and architectures that balance performance, scalability, security, and cost.
- Guide engineering teams through technical specifications, design execution, testing, and implementation while maintaining delivery quality.
- Advise clients on modernizing legacy data platforms and migrating data workloads to GCP.Leverage AI tools to accelerate analysis, synthesize complex information, and support data-driven recommendations for clients, exercising sound judgment in evaluating outputs.
- Apply AI technologies (e.g., generative AI, automation tools, data models) to enhance insights, improve delivery efficiency, and elevate the quality of client outcomes.
- Develop reusable reference architectures, accelerators, standards, and delivery methodologies for GCP and BigQuery.
- Share technical expertise and mentor colleagues to strengthen cloud data architecture and engineering capabilities.
- Stay current on Google Cloud capabilities and emerging data, analytics, and AI technologies. What You Will Bring 7+ years of experience in data engineering, data architecture, cloud architecture, or related technology roles, including experience delivering enterprise data solutions.
- Deep hands-on expertise with Google Cloud Platform and BigQuery, including data modeling, performance optimization, security, and cost management.
- Experience with relevant GCP data services such as Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer, or Dataform.
- Experience designing batch and/or streaming data pipelines and modern cloud data architectures.
- Strong knowledge of SQL, data modeling, ETL/ELT patterns, data governance, and data quality practices.
- Ability to communicate architecture decisions and tradeoffs to both technical teams and business stakeholders.
- Google Cloud Professional Data Engineer or Professional Cloud Architect certification preferred.
- Experience integrating AI tools (e.g., ChatGPT) into day-to-day workflows to enhance productivity and insight generation, coupled with strong critical thinking to assess accuracy, mitigate bias, and ensure high-quality outputs.
- Hybrid role: 2x per week in office
- Frequent travel to New York City for client work (every other week)
- Ability to work permanently in the United States without sponsorship.
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