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
Originally posted on