SMTS Data Engineer (ETL & Big-Data)

As a Senior Data Engineer (SMTS) with the Salesforce Engineering team, you will be working cross-functionally with engineers, architects, and product managers to build breakthrough features. You will play a crucial role in developing intelligent, data-driven tools for strategic decision-making regarding Salesforce infrastructure expenditure and capacity management. Your responsibilities will include developing, automating, enhancing, and maintaining scalable ETL pipelines. You will independently design and develop resilient and reusable automation data frameworks, lead data pipeline development, and participate in requirement gathering, design, and development of complex datasets. Additionally, you will mentor team members in all aspects of the data maturity lifecycle and collaborate with global teams across AMER and APAC. Key Responsibilities: - Develop, automate, enhance, maintain scalable ETL pipelines - Independently design & develop resilient and reusable automation data frameworks - Lead data pipeline development being delivered by multiple engineers - Lead and participate in requirement gathering, design, and development of complex datasets - Mentor team members in all aspects of the data maturity lifecycle - Work and collaborate with global teams across AMER, and APAC Qualifications Required: - Bachelors degree in Computer Science - 5+ 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 working as a technical lead/solution architect in a customer-focused team - Must be able to strategically communicate status and identify risks - Self-starter, highly motivated, able to shift directions quickly when priorities change, think through problems to come up with innovative solutions, and deliver against tight deadlines - Must be results-oriented and able to move forward with minimal direction - Experience in distributed SQL analytics engines such as Spark and Trino - Deep proficiency in Big Data technologies like Spark, Trino, Hive, Airflow, Docker - Experience working in Agile and Scrum methodology, incremental delivery, and CI/CD - Experienced in cloud provider platforms such as AWS, Azure, GCP - Experience with data visualization tools like Tableau is a Plus - Experience in FinOps engineering is a big plus This is a fantastic opportunity for someone passionate about building scalable, resilient, distributed systems that collect, process, and analyze massive volumes of operational data. Join us to be part of a modern, lean, self-governing product engineering team where you can make a significant impact by utilizing your expertise in data engineering and distributed systems.,