[Hiring] Data Engineer @University of the People

Role Description

We are looking for a Data Engineer with strong hands-on experience in building and scaling data pipelines on Google Cloud, with deep expertise in BigQuery. You will design and build production-grade data pipelines, implement efficient incremental loads using BigQuery merge patterns. The role focuses on delivering reliable, cost-optimized, and well-governed data to support analytics and reporting needs.

• Design, develop, and maintain scalable ELT/ETL data pipelines on Google Cloud Platform (GCP).
• Build and optimize BigQuery data warehouses, implementing performance and cost-optimization techniques including partitioning, clustering, materialized views, query optimization, and table optimization, while following the Medallion Architecture (Bronze/Silver/Gold layers).
• Design and implement data models for analytical workloads, following best practices for dimensional modeling, fact and dimension tables, relationships, and scalable data warehouse design.
• Develop and manage GCP Dataform workflows for SQL-based data transformation, dependency management, incremental processing, data quality validation, and automated deployment.
• Implement CI/CD practices including source control, code review, automated deployments, and managing changes across development, testing, and production environments.
• Create and maintain Google Cloud Functions and Cloud Run services to automate data ingestion, API integrations, event-driven processing, and orchestration tasks.
• Ingest, transform, and integrate data from multiple sources including Cloud Storage, REST APIs, and third-party connectors into BigQuery.
• Implement robust data quality frameworks, validation rules, automated testing, monitoring, alerting, and observability to ensure data reliability and accuracy.
• Design and maintain secure data platforms using IAM roles, service accounts, row-level security, column-level security, data masking, and governance best practices.
• Collaborate closely with business stakeholders, analysts, and reporting teams to deliver trusted, well-documented, analytics-ready datasets and semantic data models.
• Work with Dataform, Pub/Sub, Cloud Storage, BigQuery, Cloud Functions, and Looker/Power BI to deliver end-to-end cloud data solutions.
• Design, build, and maintain cloud ML data infrastructure for managing feature tables and automating data pipelines to power seamless model training, validation and deployment.
• Stay current with emerging GCP technologies, industry best practices, and architectural patterns, proactively recommending improvements to platform design, performance, security, and cost optimization.

Qualifications

• Bachelor’s degree in computer science, Engineering, or related field (or equivalent practical experience).

Requirements

• 5+ years of professional data engineering experience with strong hands-on expertise in Google BigQuery.
• Deep practical knowledge of BigQuery features including partitioning, clustering, MERGE statements for upsert/incremental loads, materialized views, scheduled queries, and cost optimization.
• Experience building end-to-end data pipelines that ingest and transform data in BigQuery.
• Strong proficiency in SQL (advanced optimization and DML) and Python (for pipeline development and automation).
• Solid understanding of data modeling, ETL/ELT patterns, and data warehousing concepts.
• Good grasp of data quality, testing, monitoring, and production reliability practices.