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Key Responsibilities: Design, develop, and maintain current 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 DevOps teams to automate deployment and monitoring of data pipelines. Additional tasks as required. Requirements Bachelors 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, p .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.