Data Engineer with SQL

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. you are aligning with a strategic partner dedicated to updating your \"Human OS\" and accelerating your growth through world-class, high-impact projects. 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. You will collaborate within an international network of expertise across 39 delivery centers worldwide, gaining exposure to complex engineering challenges that redefine industrial standards. 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.

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 a good understanding of performance engineering of code pipelines and near real time systems. Familiarity with cloud-native foundations or AI coding assistants. Languages Advanced Oral English: For seamless collaboration with global teams. Advanced Spanish. This position is available as: Remote / Hybrid / On-site (Depending on specific project needs). Sequoia Career's Page : 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