GCP Data Architect

Anblicks Inc.; Dallas (TX); On-site; USD 120,000 - 190,000; Full time

Job summary

Anblicks Inc. seeks a data platform architect to assess the client data landscape, design a GCP-based pipeline from ingestion to Power BI consumption, and document data flows, ownership, and quality issues.

You will run workshops with business and IT, define ingestion patterns (PostgreSQL CDC, REST APIs, spreadsheets), establish a multi-layer BigQuery architecture, and implement Kimball-style dimensional models for reporting.

Qualifications

• Expertise in BigQuery including modelling, partitioning and performance tuning.

Responsibilities

• Assess current client data landscape and document schemas, volumes and growth.
• Run workshops with stakeholders to capture KPIs, data ownership and SLAs.
• Design end-to-end data platform on GCP from ingestion to Power BI consumption.
• Define ingestion patterns for PostgreSQL (CDC), REST APIs and spreadsheets.
• Create BigQuery layers (Raw, Curated, Marts) and dimensional models.

Skills

BigQuery modelling

Partitioning & clustering

Performance tuning

Cost & slot management

GCP data services

PostgreSQL (CDC & replication)

Data warehousing & dimensional models

SCD & Kimball

ELT with Dataform or dbt

SQL

REST API & data integration

Power BI architecture

GCP security & governance

Terraform & CI/CD

Tools

GCS

Dataflow

Datastream

Pub/Sub

Cloud Composer

Cloud Run/Functions

Terraform

CI/CD pipelines

Job description

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.

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

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.

Required Skills:

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, Terraform and CI/CD