Data Engineer Lead

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.