Job Description
Key Responsibilities:
• Design, develop, and maintain new data capabilities and infrastructure for Mastercard's Sustainable Technology Internal Data Lake.
• Create new data pipelines, data transfers, and compliance-oriented infrastructure to facilitate seamless data utilization within on-premise/cloud environments.
• Identify existing data capability and infrastructure gaps or opportunities within and across initiatives and provide subject matter expertise in support of remediation.
• Collaborate with technical teams and business stakeholders to understand data requirements and translate them into technical solutions.
• Work with large datasets, ensuring data quality, accuracy, and performance.
• Implement data transformation, integration, and validation processes to support analytics/BI and reporting needs.
• Optimize and fine-tune data pipelines for improved speed, reliability, and efficiency.
• Implement best practices for data storage, retrieval, and archival to ensure data accessibility and security.
• 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 Dev Ops teams to automate deployment and monitoring of data pipelines.
• Additional tasks as required.
Requirements• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience as a Data Engineer / Scientist or similar role.
• Deep understanding & expertise in data engineering, ETL/ELT processes, data warehousing, and data modeling.
• Strong command of data integration techniques and data quality management.




• Hands-on experience with data technologies such as Databricks, Spark, Python, SQL, Hadoop, Airflow.
• Familiarity with cloud platforms and services, such as AWS or Azure.
• Excellent analytical, problem-solving skills and ability to provide cutting-edge data solutions.
• Exceptional interpersonal 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. Attention to detail is a must.
• Motivated self-starter with ability to excel at multi-tasking in a fast-paced environment and able to function under pressure with a high degree of initiative to drive results.
• Ability to quickly learn and implement new technologies and perform POC to explore best solutions for problem statements.
• Flexibility to work as a member of a matrix-based diverse and geographically distributed project team.
• 0.6 -1.5 years of experience in Data Engineering or Warehouse-related projects.
• Expertise in Data Engineering and Data Analysis: implementing multiple end-to-end Data Engineering or Warehouse projects in Big Data environment.
• Experience building data pipelines through Spark with Scala/Python/Java in Databricks or Hadoop environment
• Experience working with databases like MS SQL Server or Oracle, and strong SQL knowledge.
• Experience automating data flow processes in a Big Data environment using Airflow or similar tools.
• Experience working in Agile teams.
Requirements
Qualification: MBA/PGDM from reputed B-school. Experience: 20+ years in corporate sales, institutional leasing, or real estate investment. Requirements: Proven success in closing large deals and strong industry networks. Remuneration will be commensurate with qualifications and experience.

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