Lead Data Engineer

As a Lead Data Engineer at Salesforce Engineering, you will collaborate cross-functionally with engineers, architects, and product managers to develop breakthrough features for internal customers. Your role involves building stable and scalable applications, participating in a self-governing product engineering team, and engaging in various tasks from coding to testing for quality and performance. Key Responsibilities: - Develop, automate, enhance, and maintain scalable ETL pipelines. - Independently design and develop resilient and reusable automation data frameworks. - Lead data pipeline development handled by multiple engineers. - Lead and contribute to requirement gathering, design, and development of complex datasets. - Mentor team members throughout the data maturity lifecycle. - Collaborate with global teams across AMER and APAC. Qualifications Required: - Bachelor's degree in Computer Science. - 8+ years of experience in data engineering, data modeling, automation, and analytics. - Deep understanding of data engineering tech stack, database designs, associated tools, system components, internal processes, and architecture. - Experience as a technical lead/solution architect in a customer-focused team. - Strong communication skills for strategic status updates and risk identification. - Self-starter with the ability to adapt quickly, think innovatively, and meet tight deadlines. - Results-oriented with minimal direction requirement. - Proficiency in distributed SQL analytics engines like Spark and Trino. - Expertise in Big Data technologies such as Spark, Trino, Hive, Airflow, and Docker. - Familiarity with Agile and Scrum methodology, incremental delivery, and CI/CD practices. - Hands-on experience with cloud provider platforms like AWS, Azure, GCP. - Knowledge of data visualization tools like Tableau is a plus. - Background in FinOps engineering is highly advantageous.,