Aws Data Eng

Sequoia Connect LLC; Xico; Teletrabalho; MXN 900 000 - 1 800 000; Tempo integral

Resumo da oferta

Sequoia Connect LLC is seeking an AWS Data Engineer to design, build, and maintain automated ETL pipelines using Python and Airflow. You will orchestrate pipelines, optimize queries in Snowflake, and implement robust testing and security practices across AWS services.

The role requires 10+ years of hands-on experience, advanced Python and SQL skills, and experience with DBT, CI/CD, and AI IDE tools. This remote position supports collaboration across international teams and cloud-native workflows.

Qualificações

• 10+ years of total experience in data engineering or related field.
• Advanced Python concepts (structures, modules, packages, classes, inheritance, multi-threading, functional programming).
• Advanced SQL skills including complex joins, CTEs, and subqueries.
• Experience with Python unit, integration, and system testing.
• Experience implementing DBT tests for data validation.
• Deep AWS knowledge (S3, ECS, IAM) and security best practices.
• Familiarity with CI/CD using GitHub.
• Ability to write reusable Python packages.

Responsabilidades

• Design, develop, and maintain automated ETL pipelines using Python and Apache Airflow.
• Orchestrate pipelines to run in sequence or parallel; monitor and reprocess failed records.
• Troubleshoot data pipeline errors and fix issues.
• Export/Import data from formats (CSV, JSON, XML) via S3 or other cloud storage.
• Optimize SQL queries for performance in Snowflake or similar warehouses.
• Generate code via Python and Jinja templates.
• Implement CI/CD processes from scratch using GitHub.

Conhecimentos

Python

Airflow

SQL

Snowflake

DBT

GitHub CI/CD

AWS S3/ECS/IAM

Unit/Integration Testing

AI IDE tools

High-Performance Mindset

Technologist DNA

English

Spanish

Ferramentas

Apache Airflow

Snowflake

DBT

Jinja

GitHub

Descrição da oferta de emprego

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 an AWS Data Engineer:

The Challenge (Responsibilities)

• Design, develop, and maintain automated ETL pipelines using Python and Apache Airflow.
• Orchestrate different pipelines to run in sequence or parallel, tracking job pipeline runs to reprocess error records.
• Troubleshoot data pipeline errors and proactively fix issues.
• Export and Import data to/from various formats (CSV, JSON, XML) primarily from S3 or other cloud storage solutions.
• Optimize complex SQL queries for performance within data warehouse technologies, preferably Snowflake.
• Generate code using configurations with Python and Jinja templates.
• Implement CI/CD processes from scratch using GitHub.

Your Profile (Requirements)

• 10+ years of Total Experience, with a 100% hands-on approach to the required technical stack.
• Advanced proficiency in Python concepts (Code Structures, Modules, Packages, Class, SubClass, Inheritance, Multi-Threading, and Functional Programming) and experience developing reusable Python packages.
• Advanced SQL skills, including complex joins, CTEs, and subqueries.
• Proficiency in Python unit, integration, and system testing.
• Proficiency in implementing DBT tests for data validation and quality checks.
• In-depth understanding of AWS S3, ECS, and IAM, including best practices for organization and security.
• Knowledge of AWS security best practices (IAM roles, encryption standards, secure coding guidelines, DBT profiles access configurations).
• Experience utilizing AI IDE tools (e.g., Cursor, GitHub Copilot).
• 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 with AWS Lambda for serverless data processing tasks.
• Proficiency in using Apache Airflow on AWS to design, schedule, and monitor complex data flows, including integration with AWS services and DBT models (e.g., triggering DBT or EMR, reading from S3 to Redshift/Snowflake).
• Experience in API integrations to Salesforce, SFTP, SharePoint, OneDrive, etc.
• Experience creating complex DBT models (full refresh, incremental, snapshots) and custom DBT macros using Jinja and Python.
• Familiarity with AWS CloudWatch and Datadog for pipeline monitoring and workflow failure alerts.
• 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.

Keywords: AWS, Python, Snowflake, Airflow, DBT

• 10+ Years Experience, 100% Hands-on.
• Advanced Proficiency in Python concepts (Code Structures, Modules, Packages, Class, SubClass, Inheritance, Multi-Threading, Functional Programming).
• Experience developing reusable Python packages.
• Ability to write automated ETL processes and scheduling jobs like Airflow DAG.
• Troubleshoot data pipeline errors and fix issues.
• Export/Import data to/from CSV, JSON, XML from S3.
• Experience using AI IDE tools.
• Advanced SQL skills (complex joins, CTEs, subqueries).
• Experience optimizing SQL queries for Snowflake.
• Proficiency in Python unit, integration, and system tests.
• Proficiency in implementing DBT tests for data validation.
• Experience generating code using Python and Jinja templates.
• Experience in GitHub, implementing CI/CD processes from scratch.
• In-depth understanding of AWS S3, ECS, IAM.
• Knowledge of AWS security best practices, encryption, secure coding.