Google Cloud Platform Data Architect

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Job Role: Google Cloud Platform Data Architect

Location: Detroit, MI

Hire-type: Contract

Experience: 8 years | Detroit, MI (mandatory) — Remote up to 50% travel

Python

Google Cloud Platform Native

Data Warehousing

BigQuery

Data Modeling

ETL / ELT Pipelines

About The Role

As a Google Cloud Platform Data Architect at DataFactZ you will own the end-to-end design of cloud-native data warehouse and data platform solutions on Google Cloud. You will define data architecture standards, establish data modeling patterns, and lead the design of scalable ingestion and transformation pipelines — working hands-on with engineering teams to deliver production-grade data systems for enterprise clients.

Key Responsibilities

• Architect enterprise data warehousing solutions on Google Cloud Platform using BigQuery as the primary analytical platform, including logical and physical data model design
• Design and implement data modeling patterns: star schema, snowflake, data vault, and wide-table approaches optimized for BigQuery performance and cost
• Define lakehouse architectures across BigQuery and Cloud Storage using Parquet, Avro, and ORC formats with appropriate partitioning and clustering strategies
• Lead the design of batch and streaming ingestion pipelines using Dataflow (Apache Beam), Dataproc (PySpark), Pub/Sub, and BigQuery Data Transfer Service
• Establish transformation layer standards using dbt or Python-based ELT patterns within BigQuery
• Design pipeline orchestration frameworks using Cloud Composer (Airflow) for complex multi-step workflows
• Define data governance standards: schema management, data lineage, access controls, and partitioning policies across Google Cloud Platform projects
• Lead technical discovery with client stakeholders, produce architecture decision records, and translate business requirements into data platform designs
• Mentor data engineers and ensure adherence to architecture standards across delivery teams
  
  

Required Skills

• Python: Advanced proficiency for pipeline development, data transformation scripts, and Google Cloud Platform SDK/API integrations
• Google Cloud Platform expertise: Deep hands-on experience with BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and Cloud SQL
• Data warehousing: Proven experience designing enterprise-scale data warehouses with dimensional and vault modeling techniques
• Data modeling: Strong ability to design logical and physical models for analytical and operational workloads on BigQuery
• ETL/ELT pipelines: Designing and overseeing large-scale batch and streaming data pipelines for structured and semi-structured data
• SQL: Expert-level BigQuery SQL including window functions, nested/repeated fields, partitioning, and query optimization
• Leadership: Ability to lead architecture decisions, align cross-functional teams, and mentor engineers
  
  

Preferred

• Google Cloud Platform certifications: Professional Data Engineer or Professional Cloud Architect
• Experience with dbt Cloud for BigQuery transformation and documentation
• Familiarity with data catalog tools: Dataplex, Data Catalog, or Collibra on Google Cloud Platform
• Exposure to real-time analytics patterns using BigQuery streaming inserts or Bigtable