Data Architect

About the role

Data Architect specializing in GCP, BigQuery, and Power BI with 10+ years of experience in data engineering and architecture, including 4+ years designing data platforms on GCP.

Responsibilities

• Discovery and assessment
  • Assess the current client data landscape: the PostgreSQL schemas, volumes and growth; the third-party spreadsheets; the REST API integrations; and the HTML sources.
  • Run workshops with business owners, product, IT, security and report consumers.
  • Capture KPIs, reporting needs, data freshness SLAs and pain points.
  • Document current data flows, dependencies, data ownership and data quality issues.
• Target architecture design
  • Design the end-to-end data platform on GCP: ingestion, landing zone (GCS), BigQuery warehouse, transformation, semantic layer and Power BI consumption.
  • Define an ingestion pattern for each source type:
    • PostgreSQL: CDC or incremental loads (for example, Datastream)
    • REST APIs: Cloud Run or Cloud Functions with Pub/Sub or Cloud Scheduler
    • Spreadsheets: GCS or Google Sheets with schema validation
    • HTML files: parsing and extraction pipelines
  • Define the BigQuery layers (Raw → Curated → Marts), naming conventions and how datasets and projects are organized.
  • Design dimensional data models (star schemas and SCD handling) optimized for Power BI.
  • Pick the orchestration and transformation stack (Cloud Composer, Dataform/dbt, Dataflow) and record each choice in Architecture Decision Records.
• Scalability, performance and cost
  • Plan capacity for 10–20% monthly growth. That rate takes ~1 TB to roughly 3–9 TB within 12 months.
  • Set standards for partitioning, clustering, materialized views, BI Engine and query optimization.
  • Recommend a BigQuery pricing model (on-demand or Editions/slot reservations), storage lifecycle policies and cost guardrails.
• Power BI integration
  • Define the connectivity approach (Import, Direct Query or Composite), gateway needs and refresh strategy, including incremental refresh.
  • Guide semantic model design, row-level security (RLS) and workspace/deployment strategy.
• Security, governance and quality
  • Design IAM, VPC Service Controls, CMEK encryption, and column- and row-level security (policy tags).
  • Set up cataloguing, lineage and metadata management (Dataplex), plus PII classification and masking.
  • Define a data quality and observability framework: validation, reconciliation and alerting.
• Delivery enablement
  • Produce the architecture blueprint, HLD/LLD, NFRs (SLA, HA, DR, RPO/RTO), a phased roadmap and cost and effort estimates.
  • Define environment strategy (Dev/QA/Prod), CI/CD and Terraform (Infrastructure-as-Code) standards.
  • Hand over to the Tech Lead and act as design authority during implementation.
  • Present architecture options and trade-offs to client leadership.

Technical Skills

• Must have
  • Expert in BigQuery: modelling, partitioning/clustering, performance tuning, cost and slot management
  • GCP data services: GCS, Dataflow, Datastream, Pub/Sub, Cloud Composer, Cloud Run/Functions
  • Deep PostgreSQL knowledge: CDC/logical replication, migrating TB-scale datasets
  • Data warehousing and dimensional modelling (Kimball), SCD, medallion architecture
  • ELT with Dataform or dbt, plus strong SQL
  • Integrating REST APIs, spreadsheets and semi-structured and HTML data
  • Power BI architecture: semantic models, DirectQuery vs Import, gateways, RLS, performance with BigQuery
  • GCP security and governance: IAM, VPC-SC, K