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Data Engineer Location: Onsite - AbuDhabi UAE Employment Type: Full-Time Department: Engineering / Data & AI About the Role We are looking for a skilled Data Engineer to build, optimize, and maintain scalable data infrastructure that powers analytics, AI, and machine learning products. You will be responsible for designing robust data pipelines, integrating data from multiple sources, ensuring data quality, and enabling data accessibility across the organization. This role is ideal for someone who enjoys solving complex data challenges, building modern data platforms, and working closely with software engineers, data scientists, and product teams to transform raw data into business value. Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data. Build and manage modern data warehouses and data lakes. Develop reliable batch and real-time data processing pipelines. Integrate data from APIs, databases, third-party platforms, and cloud services. Ensure high standards of data quality, integrity, security, and governance. Optimize data models and database performance for analytics and reporting. Monitor, troubleshoot, and improve data pipeline reliability and performance. Collaborate with Data Scientists, ML Engineers, Product Managers, and Software Engineers to deliver data solutions. Implement CI/CD practices and infrastructure automation for data workflows. Document data architecture, pipeline designs, and engineering best practices. Stay current with emerging technologies in cloud data engineering and big data ecosystems. Requirements Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field. 4+ years of experience in Data Engineering or Backend/Data Platform development. Strong proficiency in Python and SQL. Experience building ETL/ELT pipelines using modern orchestration tools such as Airflow, Prefect, or Dagster. Strong knowledge of relational and NoSQL databases including PostgreSQL, MySQL, MongoDB, or Cassandra. Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, Amazon Redshift, or Azure Synapse. Experience with distributed data processing frameworks such as Apache Spark. Familiarity with message streaming technologies such as Kafka or RabbitMQ. Experience with Docker, Kubernetes, and CI/CD pipelines. Strong understanding of data modeling, partitioning, indexing, and performance optimization. Experience working with Git and collaborative software development workflows. Preferred Qualifications Experience building data platforms supporting AI or Machine Learning workloads. Knowledge of Delta Lake, Apache Iceberg, or Apache Hudi. Experience with dbt for analytics engineering. Familiarity with Terraform or Infrastructure as Code. Understanding of data governance, metadata management, and data cataloging. Experience working in high-growth technology or AI companies. Technical Stack Languages: Python, SQL Databases: PostgreSQL, MySQL, MongoDB Data Processing: Apache Spark, Pandas Orchestration: Apache Airflow, Prefect, Dagster Streaming: Kafka, RabbitMQ Cloud: AWS, Azure, GCP Data Warehouse: Snowflake, BigQuery, Redshift, Synapse Containerization: Docker, Kubernetes Version Control: Git Infrastructure: Terraform (preferred) What We're Looking For Strong analytical and problem-solving skills. Excellent understanding of scalable data architecture. Ability to work independently in a fast-paced environment. Strong communication and collaboration skills. Passion for building reliable, high-performance data systems. Continuous learning mindset and enthusiasm for modern data technologies. Nice to Have Experience supporting Generative AI or LLM applications. Experience with vector databases such as Pinecone, Weaviate, or Milvus. Familiarity with data observability platforms such as Monte Carlo or Great Expectations. Experience with event-driven architectures and real-time analytics. Exposure to MLOps platforms and feature stores. Why Join Us? Work on cutting-edge AI and data-driven products. Collaborate with a highly skilled engineering team. Opportunity to influence the architecture of modern data platforms. Exposure to large-scale cloud infrastructure and advanced analytics. Competitive compensation and significant opportunities for professional growth.
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.