Data Engineer Lead

Role Overview: We are seeking a highly experienced Senior Data Engineer with over 15 years of expertise in designing, building, and managing scalable data solutions. The ideal candidate will have extensive hands-on experience with Google Cloud Platform (GCP) services, particularly BigQuery, and a strong background in data pipelines, ETL/ELT processes, and data architecture.This role requires a strategic thinker who can lead complex data engineering projects, mentor junior team members, and collaborate with cross-functional teams to deliver high-quality data solutions.

Key Responsibilities: Design, develop, and maintain scalable and efficient data pipelines and ETL/ELT workflows using GCP services. Architect and implement data warehouse solutions using BigQuery, ensuring optimal performance and cost efficiency. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights. Optimize and manage large-scale datasets, ensuring data quality, integrity, and security. Develop and enforce best practices for data governance, data modeling, and data lifecycle management. Implement streaming data solutions using tools like Dataflow, Pub/Sub, and Apache Beam. Monitor and troubleshoot data pipelines, ensuring high availability and reliability. Lead the migration of on-premise data systems to GCP, ensuring seamless integration and minimal downtime. Mentor and guide junior engineers, fostering a culture of continuous learning and innovation. Stay updated with the latest advancements in GCP and data engineering technologies, and recommend improvements to existing systems.

Requirements What we are looking for: 15+ years of experience in data engineering, with a focus on cloud-based solutions. Expertise in GCP services, including but not limited to:BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer (Airflow), Cloud Functions. Strong proficiency in SQL and experience with BigQuery SQL for complex queries and performance optimization. Hands-on experience with Python or Java for building data pipelines and automation. Deep understanding of data modeling, data warehousing, and schema design. Experience with streaming data processing and tools like Apache Beam or Kafka. Familiarity with CI/CD pipelines and version control systems like Git. Strong knowledge of data security and compliance standards (e.g., GDPR, HIPAA). Proven experience in migrating on-premise data systems to GCP. Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment. Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.