Job Summary

As the Data Engineer, you will own the development and execution of innovative data products, solutions, and frameworks. Your expertise will ensure effective democratization of Mastercard's data using well-designed data products and solutions. You will collaborate with cross-functional teams and implement data-related best practices in alignment with Mastercard standards.

Key Responsibilities

• Design, develop, and maintain new data products, solutions, and infrastructure

• Create new data pipelines and compliance-oriented infrastructure to facilitate seamless data hydration in AWS Databricks environment.

• Collaborate with technical teams and business stakeholders to understand data requirements and translate them into technical solutions.

• Work with large card payment datasets, ensuring data quality, accuracy, and performance.

• Build and maintain data quality checks and pipeline monitoring (e.g., validation rules, anomaly detection, alerts, and dashboards) to ensure reliable, timely data delivery.

• Implement data transformation, integration, and validation processes to support analytics and BI reporting needs.

• Optimize and fine-tune data pipelines for improved speed, reliability, and efficiency.

• Troubleshoot and resolve data-related issues, collaborating with the team to identify root causes.

• Document data processes, data lineage, and technical specifications for future reference.

• Participate in code reviews, ensuring adherence to coding standards and best practices.

• Collaborate with DevOps teams to automate deployment and monitoring of data pipelines.

Skill Requirements

• Bachelor’s degree in computer science, Engineering, Data Science, or a related field.

• 6 to 8 years of experience as a Data Engineer or similar role, implementing multiple end-to-end data engineering, data lake, and data warehousing projects in a big data environment, with a strong command of data integration techniques and data quality management.

• Strong experience building Spark data pipelines using Python in Databricks

• Deep understanding & expertise in data engineering, ETL/ELT processes, data warehousing, and data modelling.

• Experience automating data pipelines in a Databricks environment using Delta Live Tables or similar tools.

• Strong experience with data technologies such as Databricks, Spark, Python, and SQL, as well as cloud platforms and services such as AWS.

• Excellent analytical, problem-solving skills and ability to provide innovative data solutions.

• Motivated initiative-taker with ability to excel at multi-tasking in a challenging environment and able to function under pressure with a high degree of initiative to drive results.

• Exceptional people skills with proven experience in relationship building and partnering, must work well in both team/individual settings and must be able to work with a geographically dispersed team.

• Strong written and oral communication skills with attention to detail

• Flexibility to work as a member of a matrix-based diverse and geographically distributed project team.

• Experience working in Agile teams.

Other Requirements

1.Relevant certifications in Azure Data Factory, Azure Databricks, SQL, Oracle, or Python would be a plus.