Senior GCP Data Engineer/Data Architect Consultant

iScale Solutions · United States · posted today ago

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About this role

Category: IT Services

Location:

Key Responsibilities

Assess the existing data pipeline, GCP architecture, data sources, and current limitations.
Design a BigQuery-based medallion architecture: Bronze, Silver, Gold, and Serving layers.
Design and/or implement data ingestion pipelines from Cloud Storage and Cloud SQL / MySQL into BigQuery.
Define BigQuery datasets, tables, partitioning, clustering, and cost-control strategies.
Support batch, incremental, and on-demand processing patterns.
Design curated and BI-ready datasets for analytics and reporting.
Support data quality checks, validation, logging, monitoring, and reprocessing patterns.
Define integration patterns for Elasticsearch or other search / serving layers.
Support architecture for AI enrichment, embeddings, semantic search, and media metadata where required.
Prepare technical documentation, architecture diagrams, implementation roadmap, and handover materials.
Work closely with client engineering, data, DevOps, and product teams.

Required Skills

Strong hands-on experience with Google Cloud data services.
Strong BigQuery experience, including modeling, optimization, partitioning, clustering, and cost control.
Experience with Cloud Storage ingestion patterns.
Experience with Cloud SQL / MySQL to BigQuery integration.
Experience building batch and incremental data pipelines.
Experience with Dataform, dbt, Cloud Composer / Airflow, Dataflow, Cloud Run, or similar tools.
Strong SQL and data modeling skills.
Good understanding of lakehouse / medallion architecture.
Experience with data quality, metadata, lineage, logging, and monitoring.
Ability to work in an ambiguous consulting environment and translate high-level requirements into practical implementation plans.
Strong communication skills and client-facing experience.

Preferred Skills

Experience with Elasticsearch or search index publishing.
Experience with Power BI-ready datasets or analytical serving layers.
Experience with Vertex AI, Gemini, embeddings, vector search, or semantic search.
Experience with media, social media, marketing, campaign, influencer, or audience data.
Experience with Dataplex, Data Catalog, IAM, policy tags, row-level security, or column-level security.
Experience with CI/CD for data pipelines.