The Role
Designs end-to-end GCP data platforms using BigQuery, GCS, ingestion pipelines, dimensional models, Power BI, and governance controls. Assesses existing data environments, defines architecture and standards, plans scalability and cost management, establishes security and data quality frameworks, and produces architecture blueprints, roadmaps, estimates, and implementation guidance. Partners with stakeholders and executives to facilitate workshops, explain trade-offs, and act as design authority during delivery.
Summary Generated by Built In
Data Architect – GCP / BigQuery / Power BI
Experience: 10+ years in data engineering and architecture, including 4+ years designing data platforms on GCP
Key ResponsibilitiesDiscovery 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.
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, KMS, policy tags, Dataplex
- Terraform and CI/CD
Good to have
- GCP Professional Cloud Architect or Professional Data Engineer certification
- Python
- Data observability tools
- Streaming analytics experience
- Telecom domain exposure
Soft skills
- Stakeholder management and workshop facilitation
- Can present trade-offs to executives
Skills Required
- 10+ years in data engineering and architecture
- 4+ years designing data platforms on GCP
- Expertise in BigQuery modeling, partitioning, clustering, performance tuning, cost management, and slot management
- Experience with GCP data services including GCS, Dataflow, Datastream, Pub/Sub, Cloud Composer, Cloud Run, and Cloud Functions
- Deep PostgreSQL knowledge, including CDC, logical replication, and TB-scale data migration
- Data warehousing and dimensional modeling expertise, including Kimball, SCD, and medallion architecture
- ELT experience with Dataform or dbt and strong SQL skills
- Experience integrating REST APIs, spreadsheets, semi-structured data, and HTML data
- Power BI architecture experience, including semantic models, DirectQuery, Import, gateways, RLS, and BigQuery performance
- GCP security and governance experience with IAM, VPC Service Controls, KMS, policy tags, and Dataplex
- Experience with Terraform and CI/CD
- Stakeholder management and workshop facilitation skills
- Ability to present architecture trade-offs to executives
- GCP Professional Cloud Architect or Professional Data Engineer certification
- Python experience
- Experience with data observability tools
- Streaming analytics experience
- Telecom domain exposure
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Anblicks is a Cloud Data Analytics Company based out of Dallas, TX, with offices in USA, India, and Australia. Since 2004, Anblicks has been helping customers by bringing value to their data and implementing modern data architecture and advanced analytics solutions in the cloud.
