Lead Data Engineer

Lead Data Engineer role designing, building, and optimizing scalable cloud-based data platforms and processing pipelines for enterprise-grade applications.

Requirements

• Design and develop scalable ETL/ELT pipelines using Google Cloud Platform services
• Build and maintain real-time and batch data processing pipelines using Apache Beam and Google Dataflow
• Develop backend processing components and data transformation services using Java
• Work extensively with BigQuery for data warehousing, analytics, querying, and performance optimization
• Integrate data from multiple sources including APIs, relational databases, streaming systems, and cloud platforms
• Build reliable and scalable streaming data pipelines using technologies such as Kafka and cloud-native services
• Optimize pipeline performance, scalability, reliability, and cloud infrastructure costs
• Ensure high standards of data quality, governance, monitoring, security, and operational excellence
• Collaborate with cross-functional teams including Architects, Analysts, DevOps, and business stakeholders to deliver data-driven solutions
• Troubleshoot production issues, perform root-cause analysis, and implement long-term scalable fixes
• Implement CI/CD practices, version control workflows, and automated deployment pipelines for data engineering solutions
• Design and maintain scalable data models, schemas, and warehouse structures
• Participate in architecture discussions and contribute to improving overall cloud data platform capabilities
• Drive best practices in distributed data processing, pipeline optimization, and cloud-native engineering

Benefits

• Paid Time Off
• Retirement Plan
• Visa Sponsorship