Big Data Engineer
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 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 structured and semi-structured JSON data.
- Implement data quality checks, monitoring, and operational support processes.
- Participate in CI/CD and version control practices for deployment and release management.
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
Your Profile (Requirements)
- Degree holders for the visa application process.
- Mid Level Dev AWS Data Engineer with 4-8 years of software development experience.
- 4-8 years of software development experience across the appropriate platform.
- Strong hands-on experience with Python, PySpark, API’s and SQL.
- Experience with ETL/data pipeline development and Orchestration using Step functions / AirFlow.
- Working knowledge of AWS services including Glue, Lambda, Step Functions, Redshift, S3, SNS, and SQS.
- Experience with Athena, EMR, Kinesis, DynamoDB, or RDS.
- Good Knowledge on CloudWatch, logging, and production support.
- Understanding of data warehousing, data lakes, Lake House and query optimization.
- Experience with GitLab/Terraform or similar and CI/CD workflows.
- 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
- Good understanding of using AI tools like Github Copilot or similar for code productivity.
- Exposure to enterprise data lake or cloud migration initiatives.
- Have an eye to solving complex problems, great communication with stakeholders.
- Have a good understanding of performance engineering of code pipelines and near real time systems.
- Good understanding on Agents and MCP.
- Familiarity with cloud-native foundations or AI coding assistants.
Languages
- Advanced Oral English: For seamless collaboration with global teams.
- Advanced Spanish.
Special Notes
- None explicitly provided in the raw JD.
Work Arrangement
We value flexibility to support your lifestyle. This position is available as:
- Remote / Hybrid / On-site (Depending on specific project needs).
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
- Mid Level Dev AWS Data Engineer with 4-8 years of software development experience
- Strong hands-on experience with Python, PySpark, API’s and SQL
- Experience with ETL/data pipeline development and Orchestration using Step functions / AirFlow
- Working knowledge of AWS services including Glue, Lambda, Step Functions, Redshift, S3, SNS, and SQS
- Experience with Athena, EMR, Kinesis, DynamoDB, or RDS
- Good Knowledge on CloudWatch, logging, and production support
- Understanding of data warehousing, data lakes, Lake House and query optimization
- Experience with GitLab/Terraform or similar and CI/CD workflows
Originally posted on