Big data Engineer (Airflow/Snowflake)

Description

Our client is a rapidly growing, automation-led service provider specializing in IT, business process outsourcing (BPO), and consulting services. With a strong focus on digital transformation, cloud solutions, and AI-driven automation, they help businesses optimize operations and enhance customer experiences. Backed by a global workforce of over 32,000 employees, our client fosters a culture of innovation, collaboration, and continuous learning, making it an exciting environment for professionals looking to advance their careers.

Committed to excellence, our client serves 31 Fortune 500 companies across industries such as financial services, healthcare, and manufacturing. Their approach is driven by the Automate Everything, Cloudify Everything, and Transform Customer Experiences strategy, ensuring they stay ahead in an evolving digital landscape. 

As a company that values growth and professional development, our client offers global career opportunities, a dynamic work environment, and exposure to high-impact projects. With 54 offices worldwide and a presence in 39 delivery centers across 28 countries, employees benefit from an international network of expertise and innovation. Their commitment to a 'customer success, first and always' philosophy ensures a rewarding and forward-thinking workplace for driven professionals.

We are currently searching for a Big data Engineer (Airflow/Snowflake):

Responsibilities:

• Design, build, and maintain ELT pipelines, orchestration, and integrations using S3, Apache Airflow, DBT Cloud, and Snowflake within an AWS cloud environment.
• Develop modular Python code for reusable packages, scripting, and automation.
• Implement and optimize SQL queries and Snowflake data models for performance and scalability.
• Deploy container-based services in AWS with proper monitoring setup.
• Integrate and process data from REST APIs to support analytical and operational needs.
• Ensure data quality, governance, and implement cloud-native troubleshooting practices.
• Collaborate with cross-functional teams to define and execute data engineering best practices.

Requirements:

• 5+ years of experience in data engineering roles.
• Proficient in Python for scripting, automation, and API interactions.
• Strong SQL skills and Snowflake expertise, including performance tuning and data modeling.
• Hands-on experience with Apache Airflow for workflow orchestration and monitoring.
• Experience with dbt for modular, version-controlled data transformations.
• Solid background with AWS services such as S3, Lambda, IAM, and CloudWatch.
• Strong understanding of data quality, governance, and troubleshooting in cloud environments.

Languages

• Advanced Oral English.
• Native Spanish.

Note:

• Fully 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: https://www.sequoia-connect.com/careers/

Requirements

Requirements:

• 5+ years of experience in data engineering roles.
• Proficient in Python for scripting, automation, and API interactions.
• Strong SQL skills and Snowflake expertise, including performance tuning and data modeling.
• Hands-on experience with Apache Airflow for workflow orchestration and monitoring.
• Experience with dbt for modular, version-controlled data transformations.
• Solid background with AWS services such as S3, Lambda, IAM, and CloudWatch.
• Strong understanding of data quality, governance, and troubleshooting in cloud environments.