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Department : Data Division : Technology You will be exposed to: Drive the implementation and optimization of centralized data repositories and data lake architectures , supporting enterprise-wide analytics and reporting. Identify, diagnose, and resolve data-related issues , ensuring data quality, integrity, and availability for downstream analytics and business applications. Apply advanced data modeling techniques to solve real-world business challenges, ensuring data consistency, integrity, and performance. Provide advanced support and troubleshooting for data pipelines, ETL/ELT processes, and data integration workflows across cloud and on-prem environments. Enhance and mentor others in organizational, communication, and analytical skills, fostering a collaborative and data-driven engineering culture. Gain exposure to the end-to-end machine learning lifecycle, from experimentation to production, by enabling robust and scalable data access for model training and inference. Key responsibilities: Develop, optimize, and maintain robust data pipelines(ETL/ELT) across both on-premise and cloud environments Work closely with business and technical teams to ensure that data mapping aligns with business rules and reporting needs Maintain data lake and data warehouse solutions Develop detailed reports and documentation of incidents and resolutions to contribute towards continuous improvement processes within the team Create and maintain data mapping documents to define the relationships between source data and target schemas. Develop and support the ingestion of data from multiple sources into a centralized data repository or data lake . Perform basic data cleaning, transformation, and validation to ensure data quality and integrity. Requirements: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field. 2 years of experience in data engineering, data warehousing, or big data environments Strong understanding of data structures, performance tuning, and optimization. Strong proficiency in SQL and one or more programming languages (Python, Java, or Scala). Ability to troubleshoot and improve complex data workflows. Experience designing systems for scalability, reliability, and maintainability . Strong communication and documentation skills. Solid understanding of data governance, security, and compliance principles. Strong communication and documentation skills. Exposure to BI tools such as Power BI, Tableau, or Looker for data consumption and visualization. Exposure to Machine Learning projects implementation Nice to have: Experience with streaming platforms
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.