Lead Google Cloud Platform Solution Architect 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., * 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

• 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