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We are looking for data engineers who have the right attitude, aptitude, skills, empathy, compassion, and hunger for learning. Build products in the data analytics space. A passion for shipping high-quality data products, interest in the data products space; curiosity about the bigger picture of building a company, product development and its people. Roles and Responsibilities Develop and manage robust ETL pipelines using Apache Spark (Scala) Understand park concepts, performance optimization techniques and governance tools Develop a highly scalable, reliable, and high-performance data processing pipeline to extract, transform and load data from various systems to the Enterprise Data Warehouse/Data Lake/Data Mesh Collaborate cross-functionally to design effective data solutions Implement data workflows utilizing AWS Step Functions for efficient orchestration. Leverage AWS Glue and Crawler for seamless data cataloging and automation Monitor, troubleshoot, and optimize pipeline performance and data quality Maintain high coding standards and produce thorough documentation. Contribute to high-level (HLD) and low-level (LLD) design discussions Technical Skills Minimum 3 years of progressive experience building solutions in Big Data environments. Have a strong ability to build robust and resilient data pipelines which are scalable, fault tolerant and reliable in terms of data movement. 3+ years of hands-on expertise in Python, Spark and Kafka. Strong command of AWS services like EMR, Redshift, Step Functions, AWS Glue, and AWS Crawler. Strong hands on capabilities on SQL and NoSQL technologies. Sound understanding of data warehousing, modeling, and ETL concepts Familiarity with High-Level Design (HLD) and Low-Level Design (LLD) principles Excellent written and verbal communication skills. Role: Data Engineer Industry Type: IT Services & Consulting Department: Data Science & Analytics Employment Type: Full Time, Permanent Role Category: Data Science & Machine Learning Education UG: Any Graduate
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.