Data Engineer

Data Engineer at PayPal in Chennai, India

PayPal is seeking a talented Data Engineer to join our team in Chennai, Tamil Nadu, India. This role offers a significant opportunity to impact our business through robust data solutions. You will be instrumental in designing, developing, and maintaining efficient data pipelines, scalable data storage, and ensuring data quality and consistency. Your work will involve implementing data transformation techniques, collaborating with cross-functional teams to understand and meet data requirements, and optimizing data engineering processes for performance and reliability. You will work with large datasets to support the monitoring of key business metrics and generate valuable insights for decision-making. This position involves assisting in the implementation of data quality checks and monitoring solutions, collaborating with senior engineers on data infrastructure enhancements, and contributing to projects focused on risk management and process optimization using data-driven solutions. You will develop a working knowledge of the business domain and support communication with stakeholders to clarify requirements, share updates, and align on project goals. Collaboration with analysts and other stakeholders will be key to uncovering insights that support operational and business decisions.

Responsibilities:

• Design and develop data pipelines for efficient data collection and processing.
• Build and maintain scalable data storage solutions.
• Ensure data quality and consistency through validation and cleansing processes.
• Implement data transformation techniques to prepare data for analysis.
• Collaborate with cross-functional teams to understand data requirements and provide solutions.
• Optimize data engineering processes for performance and reliability.
• Work with large datasets to support the development and maintenance of data pipelines that help monitor key business metrics and generate valuable insights for decision-making.
• Assist in implementing data quality checks and monitoring solutions to ensure data integrity, consistency, and reliability across key pipelines.
• Collaborate with senior engineers in maintaining and enhancing the data infrastructure, ensuring automation and efficiency in data processing workflows.
• Contribute to projects focused on risk management and process optimization by applying data-driven solutions to solve specific business problems.
• Carry out assignments with moderate complexity under guidance, while continuously looking for ways to improve data processes and outputs.
• Develop a working knowledge of the business domain to support data initiatives within a broader strategic context.
• Support communication with cross-functional teams to clarify requirements, share updates, and align on project goals.
• Collaborate with analysts and other stakeholders to help uncover insights that support operational and business decisions.

Qualifications:

• Minimum of 2 years of relevant work experience and a Bachelor's degree or equivalent experience.
• 2-5 years of experience in data engineering, working with large-scale data processing systems.
• Strong experience in BigQuery, SQL, and Python, with knowledge of Spark.
• Familiarity with Google Cloud Platform services such as BigQuery, Cloud Storage, Dataflow, or Dataproc is a plus.
• Good understanding of data modeling concepts and ability to document data workflows effectively.
• Experience participating in Business Intelligence and data pipeline projects, including gathering requirements and analyzing structured data sets.
• Comfort with statistical thinking, attention to detail, and a problem-solving mindset.
• Exposure to domains like payments, e-commerce, or financial services is beneficial but not required.
• Self-driven and enthusiastic about learning and growing within a fast-paced environment.
• Able to work well both independently and as part of a team.
• Strong communication skills, with the ability to collaborate across teams and present findings clearly.
• Organized and thoughtful, with a focus on execution and follow-through on assigned tasks.