Python Data Engineer - Remote

Overview

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.

In Short

• Design, build, and optimize scalable data pipelines for ETL processes.
• Develop and maintain data integration workflows using Python and SQL.
• Collaborate with data analysts and stakeholders to translate business requirements into technical solutions.
• Ensure data quality, reliability, and performance across databases and systems.
• Document data engineering processes, architectures, and best practices.

Requirements

• 5–8 years of experience in data engineering or related roles.
• Expertise in Python for data processing and automation.
• Strong SQL skills for complex querying and database management.
• Proven experience with ETL development and data pipeline optimization.
• Familiarity with cloud-based data platforms (e.g., Snowflake is a plus).

Benefits

• Global career opportunities.
• Dynamic work environment.
• Exposure to high-impact projects.
• International network of expertise and innovation.
• Rewarding workplace culture focused on customer success.