Design, build, and evolve cloud-native data platform on Google Cloud Platform. Define architectural vision for data flow, storage, processing, and consumption across organization. Partner with engineering, analytics, and business stakeholders to shape data infrastructure quality, reliability, and scalability.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
Job Title - GCP Data Architect
Location-**remote**
** Visa independent only**
We are looking for an experienced GCP Data Architect to design, build, and evolve our cloud-native data platform on Google Cloud Platform. You will define the architectural vision for how data flows, is stored, processed, and consumed across the organization — partnering closely with engineering, analytics, and business stakeholders.
This is a high-impact role where your decisions will directly shape the quality, reliability, and scalability of our data infrastructure for years to come.
Responsibilities
** Occasional travel to Brazil**
- Design and own the end-to-end data architecture on GCP, including ingestion, storage, transformation, and serving layers
- Define standards for data modeling, pipeline design, and data quality across all GCP data products
- Architect solutions using BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, and Looker
- Lead the adoption of best practices for data governance, security, and compliance (PII handling, IAM, VPC-SC)
- Collaborate with data engineering teams to review designs and ensure alignment with the reference architecture
- Evaluate and introduce new GCP-native tools and features to improve platform performance and cost efficiency
- Drive data catalog adoption and metadata management using Dataplex and Data Catalog
- Partner with stakeholders to translate business requirements into scalable architectural blueprints
- Mentor engineers and promote architectural thinking across the data organization
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Required qualifications
- 7+ years in data engineering or data architecture roles
- 4+ years of hands-on GCP experience in a production environment
- Deep expertise in BigQuery, including optimization and data modeling
- Strong knowledge of streaming (Dataflow/Pub/Sub) and batch processing patterns
- Experience with dbt, Apache Beam, or Spark on GCP
- Proficiency in SQL and Python
- Familiarity with Terraform or other IaC tools for GCP
- Strong understanding of data mesh, data lakehouse, or medallion architectures
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