Data Engineer

5 - 9 years

0 Lacs

Posted:2 days ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

As a Lead Data Engineer at Mastercard, you will be a key player in the Mastercard Services Technology team, responsible for driving the mission to unlock the potential of data assets by innovating, managing big data assets, ensuring accessibility of data, and enforcing standards and principles in the Big Data space. Your role will involve designing and building scalable, cloud-native data platforms using PySpark, Python, and modern data engineering practices. You will mentor and guide other engineers, foster a culture of curiosity and continuous improvement, and create robust ETL/ELT pipelines that integrate with various systems. Your responsibilities will include decomposing complex problems into scalable components aligned with platform goals, championing best practices in data engineering, collaborating across teams, supporting data governance and quality efforts, and optimizing cloud infrastructure components related to data engineering workflows. You will actively participate in architectural discussions, iteration planning, and feature sizing meetings while adhering to Agile processes. To excel in this role, you should have at least 5 years of hands-on experience in data engineering with strong PySpark and Python skills. You must possess solid experience in designing and implementing data models, pipelines, and batch/stream processing systems. Additionally, a strong foundation in data modeling, database design, and performance optimization is required. Experience working with cloud platforms like AWS, Azure, or GCP and knowledge of modern data architectures and data lifecycle management are essential. Furthermore, familiarity with CI/CD practices, version control, and automated testing is crucial. You should demonstrate the ability to mentor junior engineers effectively, possess excellent communication and collaboration skills, and hold a Bachelor's degree in computer science, Engineering, or a related field. Comfort with Agile/Scrum development environments, curiosity, adaptability, problem-solving skills, and a drive for continuous improvement are key traits for success in this role. Experience with integrating heterogeneous systems, building resilient data pipelines across cloud environments, orchestration tools, data governance practices, containerization, infrastructure automation, and exposure to machine learning data pipelines or MLOps will be advantageous. Holding a Master's degree, relevant certifications, or contributions to open-source/data engineering communities will be a bonus.,

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