Data Engineer

Responsibilities

• Design robust BigQuery based data architectures that support large scale analytics and reporting needs while ensuring performance reliability and cost efficiency
• Create optimized data models and partitioning strategies in BigQuery that improve query speed, data quality, and maintainability for complex analytical workloads
• Create reusable patterns for data ingestion, transformation, and storage using BigQuery and complementary cloud native services to streamline project delivery
• Implement query optimization techniques including clustering, indexing alternatives, and efficient SQL patterns to reduce processing time and resource consumption
• Define standards for data security, access control, and compliance within BigQuery environments to protect sensitive information and align with organizational policies
• Partner with product and business stakeholders to translate analytical requirements into practical BigQuery solutions that deliver measurable value and improved decision making
• Coverage coordination with data engineers, analysts, and platform teams to ensure consistent adoption of BigQuery best practices across projects and environments
• Develop monitoring and observability practices for BigQuery workloads using logging and metrics to detect issues early and ensure stable system performance
• Prepare technical design documents, solution diagrams, and reference guides that clearly describe BigQuery architectures and data flows for technical and nontechnical audiences
• Conduct code reviews and performance assessments for SQL scripts and data pipelines running on BigQuery to ensure adherence to standards and continuous improvement
• Provide technical guidance on migration of existing data warehouses and analytics solutions into BigQuery with a focus on risk mitigation and smooth transition
• Advise on cost management strategies such as workload sizing, storage optimization, and scheduling to ensure BigQuery usage remains sustainable and predictable