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 global IT powerhouse that represents the connected world through innovative, customer-centric experiences. As a USD 6 billion organization and one of the top 7 IT service providers globally, our client empowers over 1,200 global customers—including several Fortune 500 companies—to "Rise™." With a massive network of 163,000+ professionals across 90 countries, they are at the absolute forefront of digital transformation, leveraging next-generation technologies such as 5G, AI, Blockchain, and Quantum Computing. This is your chance to thrive in a workplace recognized as one of the most sustainable corporations in the world. You will join an environment that values innovation and societal impact, working on end-to-end digital transformation projects for global leaders. If you are a driven professional looking for global career opportunities and exposure to high-impact projects within an international network of expertise, this is where you belong. We are currently searching for a Data Engineer Lead: Our Client is looking for a Lead Data Engineer who will help in implementing data analytics products using on-prem and cloud data platforms. The Challenge (Responsibilities) • Design and build scalable, cloud-native data platforms for modern data engineering practices. • Mentor and guide other engineers, sharing knowledge, reviewing code, and fostering a culture of curiosity, growth, and continuous improvement. • Create robust, maintainable ETL/ELT pipelines that integrate with diverse systems and serve business-critical use cases. • Lead by example—write high-quality, testable code and participate in architecture and design discussions with a long-term view in mind. • Decompose complex problems into modular, efficient, and scalable components that align with platform and product goals. • Support data governance and quality efforts, ensuring data lineage, cataloging, and access management are built into the platform. • Participate in architectural discussions, iteration planning, and feature sizing meetings. Your Profile (Requirements) • Strong hands-on experience in data engineering building production-grade pipelines on big data platforms (Hadoop ecosystem and cloud data platforms - databricks). • High proficiency in using Python, Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi), SQL to build Big Data products. • Hands-on experience with cloud data platforms such as databricks, snowflake (databricks preferred). • Experience with orchestration/integration tools such as Apache Airflow, Apache NiFi, or Talend. • Working knowledge of DevOps/CI-CD practices: version control (Git), automated testing, release pipelines, and observability. • Strong problem-solving skills with the ability to debug complex data issues and communicate clearly with technical and non-technical stakeholders. • 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 developing Java based applications. • Familiarity with cloud-native foundations or AI coding assistants. Languages • Advanced Oral English: For seamless collaboration with global teams. • Advanced Spanish. Work Arrangement We value flexibility to support your lifestyle. This position is available as: • 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: Requirements • Strong hands-on experience in data engineering building production-grade pipelines on big data platforms (Hadoop ecosystem and cloud data platforms - databricks). • High proficiency in using Python, Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi), SQL to build Big Data products. • Hands-on experience with cloud data platforms such as databricks, snowflake (databricks preferred). • Experience with orchestration/integration tools such as Apache Airflow, Apache NiFi, or Talend. • Working knowledge of DevOps/CI-CD practices: version control (Git), automated testing, release pipelines, and observability. • Strong problem-solving skills with the ability to debug complex data issues and communicate clearly with technical and non-technical stakeholders. Originally posted on Himalayas