Big Data Lead

Description At Sequoia Connect , we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects. We are currently partnering with a rapidly growing, automation-led powerhouse that serves 31 Fortune 500 companies across the financial, healthcare, and manufacturing sectors. With a global workforce of over 32,000 employees and a presence in 28 countries, our client is a titan of digital transformation. Their "Automate Everything, Cloudify Everything" strategy ensures you will be working at the absolute forefront of AI-driven automation and cloud solutions. This is your chance to thrive in a "Customer Success, First and Always" environment that prizes continuous learning and radical ownership. You will collaborate within an international network of expertise across 39 delivery centers worldwide, gaining exposure to complex engineering challenges that redefine industrial standards. If you are a driven professional looking for a dynamic, forward-thinking workplace where your growth is the priority, this is where you belong. We are currently searching for a Big Data Lead : Responsibilities Develop and support data integration, ELT, and data engineering solutions. Process large data volumes in distributed or cloud-based environments. Design resilient data pipelines incorporating logging, monitoring, retry logic, idempotency, and failure recovery. Work within a modern data engineering ecosystem including cloud storage, data lakes, data warehouses, and distributed compute platforms. Utilize streaming systems, APIs, orchestration tools, source control, automated testing, and observability platforms. Implement containerization, deployment technologies, CI/CD pipelines, and Infrastructure as Code (IaC). Lead data modeling, metadata management, data governance, and master data management practices. Requirements Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (equivalent practical experience considered). 5 years of experience developing and supporting data integration, ELT, or data engineering solutions. Strong proficiency in SQL. Proficiency in at least one programming language such as Python, Java, Scala, or Spark SQL. Experience with orchestration and workflow tools (Apache Airflow, Azure Data Factory, AWS Step Functions). Working knowledge of relational and non-relational databases, data warehouses, and data lake architectures. Experience with the AWS cloud data platform, including AWS Lambda and KAFKA. Strong analytical, troubleshooting, communication, and collaboration skills. High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery. Technologist DNA: A deep understanding of the difference between "coding" and "engineering." Desired Experience working in regulated, financial services, healthcare, or other highly controlled environments. Familiarity with cloud-native foundations or AI coding assistants. Languages Advanced Oral English. Advanced Spanish. Note: Fully remote. If you meet these qualifications and are pursuing new challenges, start your application on our website to join an award-winning employer. Explore all our job openings | Sequoia Career’s Page : https://www.sequoia-connect.com/careers/ Requirements Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (equivalent practical experience considered). 5 years of experience developing and supporting data integration, ELT, or data engineering solutions. Strong proficiency in SQL. Proficiency in at least one programming language such as Python, Java, Scala, or Spark SQL. Experience with orchestration and workflow tools (Apache Airflow, Azure Data Factory, AWS Step Functions). Working knowledge of relational and non-relational databases, data warehouses, and data lake architectures. Experience with the AWS cloud data platform, including AWS Lambda and KAFKA. Strong analytical, troubleshooting, communication, and collaboration skills. High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery. Technologist DNA: A deep understanding of the difference between "coding" and "engineering."