At Sequoia Connect, we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the integral 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 Engineer:
The Challenge (Responsibilities)
- Build and maintain ETL pipelines using Python and PySpark on AWS Glue and related platforms.
- Orchestrate workflows using AWS Step Functions and Lambda.
- Implement messaging and event-driven integrations using SNS and SQS.
- Design and optimize storage and querying solutions in Amazon Redshift, RDS, Oracle and S3-based architectures.
- Write efficient SQL for transformations, validation, and reporting.
- Integrate data from APIs and process structur

📌 Big Data Engineer (México)
🏢 Sequoia Connect
📍 México