Cloud Data Loading Architect

Role Summary

We are looking for an experienced Cloud Data Loading Architect to design, build, and optimize scalable data ingestion pipelines on Google Cloud Platform (GCP), with a strong focus on BigQuery.

The ideal candidate will lead end-to-end data ingestion architecture—from source discovery and schema mapping to transformation, validation, and high-performance loading into cloud-native data warehouses. This role requires a combination of strong cloud engineering expertise, hands-on data integration experience, and deep knowledge of BigQuery performance optimization.

Key Responsibilities

• Design and implement high-throughput, fault-tolerant ingestion pipelines for both batch and streaming data into BigQuery.
• Architect data ingestion solutions using GCS, Dataflow (Apache Beam), Pub/Sub, Dataproc, Cloud Composer (Airflow), and BigQuery Storage Write API.
• Define data loading frameworks, schema evolution strategies, mapping rules, and metadata management processes.
• Develop reusable ingestion patterns ensuring data governance, lineage, and auditability.
• Implement data quality checks, validation rules, reconciliation logic, and SLA monitoring.
• Optimize BigQuery performance and cost through partitioning, clustering, and efficient query design.
• Collaborate with security teams to enforce IAM, VPC Service Controls (VPC-SC), encryption, and access policies.
• Automate deployment pipelines using CI/CD tools such as Cloud Build, GitHub Actions, GitLab, or Jenkins.
• Provide technical documentation and mentor engineering teams on best practices.
• Troubleshoot ingestion issues, performance bottlenecks, and cross-platform integration challenges.

Required Skills & Qualifications

Core Technical Skills

• Strong expertise in Google Cloud Data Services:
• BigQuery, GCS, Dataflow, Pub/Sub, Dataproc, Cloud Composer
• Proven experience in data ingestion and integration frameworks
• Advanced SQL and BigQuery optimization skills (partitioning, clustering, cost optimization)
• Hands-on experience with ETL/ELT tools (Airflow, Dataflow, dbt, etc.)
• Proficiency in Python and/or Java for pipeline devel

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