Senior GCP Data Engineer/Data Architect Consultant

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.

Requirements

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.

Benefits
WFH or Hybrid and competitive salary

Details
Originally posted on Himalayas