Google BigQuery Data Lake Architect Consultant; Remote

... create world-changing products using God-given talents . .

We are seeking an experienced Google Cloud / Big Query Data Lake Architect Consultant to help design and implement a modern enterprise data platform for a large omnichannel retail organization. The consultant will define the target architecture, ingestion patterns, data modeling approach, security framework, governance standards, and implementation roadmap for a Google Cloud-based data lake / lakehouse centered on Big Query.

• Initial duration: 3 to 6 months, with strong possibility of extension.
• Must be able to work in the Pacific Time Zone.
• Consulting role requiring hands‑on architecture and implementation leadership.

• 10+ years of enterprise data architecture, data engineering, or data-platform experience.
• 5+ years of significant Google Cloud Platform experience.
• Deep hands-on experience with Big Query in production environments.
• Proven experience architecting a cloud enterprise data lake, lakehouse, or modern data warehouse.
• Strong knowledge of Big Query architecture and optimization, SQL, data modeling, ELT/ETL, pipelines, APIs, CDC, streaming, data quality, metadata, lineage, and security.
• Experience designing platforms that process large transaction volumes.
• Experience with dbt and/or Dataform.
• Experience with Airflow / Cloud Composer or similar orchestration tooling.
• Experience with Git-based development and CI/CD.
• Experience implementing data governance within GCP.
• Ability to develop architecture while remaining hands‑on with engineering teams.
• Strong communication skills with technical and business stakeholders.

• Retail industry experience, especially fashion, specialty, or omnichannel retail.
• Experience implementing enterprise retail data models.
• Experience migrating from legacy merchandising / ERP platforms.
• Experience building data foundations for AI, machine learning, and GenAI.
• Snowflake experience and ability to compare Snowflake and Big Query architectural patterns.
• Experience defining semantic layers and supporting BI platforms.
• Experience managing offshore or systems‑integrator development teams.

• Design the overall Google Cloud data lake / lakehouse architecture, with Big Query as the core enterprise analytical platform.
• Define ingestion patterns for batch, near-real-time, streaming, API, file-based, and database-source integrations. Datastream, Cloud Run / Cloud Functions, dbt and/or Dataform, and Dataplex.
• Develop a strategy for ingesting data from SaaS and enterprise applications into Google Cloud.
• Establish raw, standardized, curated, and consumption data layers.
• Design enterprise data models supporting analytics, reporting, AI/ML, and GenAI use cases.
• Define Big Query standards for datasets, tables, partitioning, clustering, retention, and performance.
• Define scalable patterns for historical data, incremental processing, CDC, and slowly changing dimensions.
• Establish master and reference data standards.
• Define data-quality frameworks, reconciliation controls, observability, lineage, and monitoring.
• Establish security architecture including IAM, service accounts, row‑level security, column‑level security, policy tags, encryption, PII protection, and environment separation.
• Establish Big Query cost‑management and optimization practices.
• Develop standards for CI/CD, infrastructure as code, testing, deployment, and environment management.
• Work across BI, data engineering, application, infrastructure, security, and business teams.
• Provide technical leadership and mentoring to internal engineering resources and implementation partners.
• Develop a phased migration and implementation roadmap.

Work your way
– Enjoy the freedom to work from anywhere, with flexible hours that match your natural rhythm.

Work with global clients
– Collaborate directly with international teams to create real impact.

Great people, no micromanagement
– Join a supportive, results-focused team where you’re trusted to do your best work.

This flexibility allows developers…

A better work-life balance

Increased productivity

The ability to work any time around the clock