Data Engineer Lead

Role Summary

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.