Big Data Engineering 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 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 Engineering Lead:

The Challenge (Responsibilities)

Provide technical leadership, engineering delivery, and quality assurance for the Data Foundation platform.

Lead the team responsible for building and maintaining enterprise data pipelines, data products, canonical data models, and data services to enable analytics, AI, integration, and operational reporting.

Partner closely with the Service Owner, Architecture Team, and Platform Engineering Lead to deliver scalable, trusted, and maintainable data solutions aligned with enterprise standards and strategic objectives.

Take accountability for engineering execution, solution quality, operational reliability, and the development of a high-performing data engineering team.

Successfully deliver Data Foundation engineering commitments while ensuring data pipeline reliability, performance, and scalability.

Drive data quality improvements across enterprise data assets, adopt engineering standards, reduce technical debt, and improve operational stability through incident reduction.

Increase reuse of canonical data models, data products, and engineering frameworks.

Your Profile (Requirements)

8+ years of experience in data engineering, software engineering, or enterprise data platform development.

3+ years of technical leadership experience leading engineering teams or large-scale data initiatives.

Proven experience designing and delivering enterprise data platforms, pipelines, and data products.

Experience operating within agile software development environments.

Advanced SQL and data modeling expertise.

Strong Python and PySpark development experience.

Deep understanding of ETL and ELT architecture patterns.

Strong technical leadership, coaching capabilities, and problem-solving 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 implementing Master Data Management solutions.

Experience building RESTful APIs and data services.

Familiarity with GraphQL and modern integration approaches.

Understanding of microservices-based architectures.

Experience implementing event-driven and real-time data processing solutions.

Strong understanding of data quality frameworks, metadata management, and data lineage concepts.

Familiarity with cloud-native foundations or AI coding assistants.

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

• 8+ years of experience in data engineering, software engineering, or enterprise data platform development.
• 3+ years of technical leadership experience leading engineering teams or large-scale data initiatives.
• Proven experience designing and delivering enterprise data platforms, pipelines, and data products.
• Experience operating within agile software development environments.
• Advanced SQL and data modeling expertise.
• Strong Python and PySpark development experience.
• Deep understanding of ETL and ELT architecture patterns.