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We are looking for a Data Engineer to join our analytics team. You will design, build and maintain scalable data pipelines, data warehouses and cloud-based data platforms that support analytics and business decision-making. You will work closely with cross-functional teams to transform raw data into reliable, accessible datasets while improving the performance, quality and efficiency of our data systems. Responsibilities Design, build, test and maintain databases, data warehouses, data lakes and large-scale data processing systems. Develop reliable data pipelines to support analytics, data modelling and production workloads. Build and continuously improve ETL/ELT processes based on business requirements. Collect, clean and transform structured, semi-structured and unstructured data. Prepare data for descriptive, predictive and prescriptive analytics. Develop and optimise Oracle SQL, PL/SQL, stored procedures and batch jobs. Improve data quality, reliability, availability and processing efficiency. Organise and maintain data assets and catalogues for easy access and retrieval. Support routine and ad-hoc data requirements from analytics teams, stakeholders and business users. Work closely with engineering, analytics and business teams to deliver practical data solutions. Requirements Bachelor’s degree in Computer Science, Information Technology, Engineering or a related field At least 3 years of relevant experience in data engineering, data warehousing, data processing, data modelling or ETL/ELT development. Strong experience in SQL and Oracle PL/SQL development. Hands-on experience building and maintaining data pipelines and data warehouses. Experience using Python, Java or another programming language for data processing and automation. Experience working with cloud-based data platforms, preferably AWS. Familiarity with AWS services such as S3, EC2, Redshift, Athena, EMR or Kinesis. Experience with one or more data engineering technologies, such as Apache Airflow, Apache Spark, Hadoop, HDFS, Scala or Hive. Good understanding of database architecture, schema design and performance optimisation. Strong analytical, problem-solving and communication skills. Ability to work effectively with both technical and business teams. Preferred Skills Experience with real-time data streaming solutions. Familiarity with Kubernetes, containerisation and CI/CD pipelines. Experience deploying data services or microservices. Experience in data crawling, data lake development or large-scale data processing. Knowledge of machine learning, statistical modelling or algorithm development. Relevant certifications in cloud computing, data engineering, software development, databases, data science or machine learning.
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.