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Responsibilities Design, develop, test, and maintain optimal data pipeline and ETL architectures.Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.Prepare and optimise data for predictive and prescriptive modelling.Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.Enhance cloud data infrastructure on AWS or Azure for scalability and performance.Utilise big data tools and frameworks to optimise data acquisition and preparation.Build architectures to move data to/from data lakes and data warehouses for advanced analytics.Develop and curate data models for analytics, dashboards, and reports.Conduct code reviews, maintain production-level code, and implement testing approaches.Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.Drive innovation and implement efficient new approaches to data engineering tasks. Requirements Bachelor's degree in Computer Science, Mathematics, Engineering, or a related field.5+ years of experience working with enterprise data platforms, including building and managing data lakes.QX | Public: 3-5 years of experience designing and implementing data warehouse solutions.Expertise in SQL, including developing stored procedures (SPs) and applying advanced data design conceptsProficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.Experience with AWS or Azure services (e. g., AWS Glue, Azure Data Factory, Redshift, Snowflake).Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.Hands-on experience with orchestration tools (e. g., Apache Airflow, Prefect).Knowledge of CI/CD processes, version control (e. g., Git, Jenkins), and deployment automation.Strong problem-solving, communication, and collaboration skills. Good-to-Have Skills Experience in integrating ERP data into data lakes.Experience with traditional ETL tools (e. g., Talend, Pentaho). This job was posted by Gnana Ramya from QuaXigma. .
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.