Architect (ATC)

JOB DESCRIPTION - Cloud Data Loading Architect (Google Cloud / BigQuery) Role Summary We are seeking an experienced Cloud Data Loading Architect to design, build, and optimise automated pipelines that ingest structured, semistructured, and unstructured datasets into Google Cloud Platform (GCP), specifically BigQuery. This role will lead endtoend data ingestion design-from source discovery and schema mapping, through transformation and data quality, to scalable, secure loads into cloudnative analytical warehouses. The ideal candidate combines strong cloud engineering skills with handson data integration experience and a deep understanding of BigQuery performance optimisation.

Key Responsibilities  Design and implement highthroughput, faulttolerant ingestion pipelines for batch and streaming data landing in BigQuery.  Lead data ingestion architecture patterns using Cloud Storage (GCS), Dataflow, Dataproc, Composer (Airflow), Pub/Sub, BigQuery Storage Write API, and related services.

 Define data loading frameworks, mapping rules, schema evolution strategy, and metadata management.  Create reusable ingestion blueprints that ensure governance, lineage, and auditability.  Establish data quality checks, validation rules, reconciliation logic, and SLAs.  Optimise BigQuery cost, storage, partitioning, clustering, and access patterns.

�� Top 10 Skillset & Qualities (Ideal Candidate)

• Deep Expertise in Google Cloud Data Services BigQuery, GCS, Dataflow (Apache Beam), Pub/Sub, Dataproc, Cloud Composer, Storage Write API.
• Data Ingestion Engineering Mastery Handson experience designing frameworks to load data from APIs, files, databases, event streams, and mainframe/legacy systems into cloud stores.
• Strong SQL & BigQuery Optimisation Skills Partitioning, clustering, materialised views, costefficient query design, columnar storage understanding.
• ETL/ELT Architecture Knowledge Experience building transformation pipelines using Airflow, Dataflow, dbt, or equivalent orchestration tools.