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