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