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Open nowFirst seen 7 hours ago

Senior Data Engineer

Datahubanalytics5 open roles

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Your applicationOpen nowSenior Data EngineerDatahubanalytics

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The clock on this job

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11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: first seen 7 hours ago

The posting

DataHub Analytics is a fast-growing Data & AI consultancy empowering organizations to become truly data-driven. We design and implement modern data platforms, AI-powered analytics solutions, and intelligent automation systems that transform how businesses operate and make decisions.

Operating across the Middle East, we combine deep industry expertise with cutting-edge technologies to deliver scalable, secure, and future-ready data ecosystems.

The Role

We are looking for a skilled Senior Data Engineer with 4+ years of hands-on experience in designing, developing, and optimizing scalable data pipelines and data integration solutions. The ideal candidate will have strong expertise in Python, Apache Spark, Apache Kafka, and SQL, with a solid understanding of ETL/ELT processes and distributed data processing. The role involves building reliable data solutions, optimizing data workflows, and ensuring data quality and performance across large-scale data environments.

Technical Expertise

Customer Relationship

Personal Evolution

Autonomy

Responsibilities

  • Design, develop, and maintain reliable and scalable ETL/ELT data pipelines.
  • Build and optimize data processing solutions using Python and Apache Spark.
  • Develop and maintain real-time and near-real-time data pipelines using Apache Kafka.
  • Write and optimize complex SQL queries and data transformation logic.
  • Integrate data from multiple structured and unstructured data sources.
  • Design solutions for handling large volumes of data while maintaining performance, reliability, and data quality.
  • Troubleshoot data pipeline failures, performance issues, and data inconsistencies.
  • Implement monitoring, logging, error handling, and recovery mechanisms for data pipelines.
  • Collaborate with data architects, analysts, application teams, and business stakeholders to understand and translate data requirements into technical solutions.
  • Participate in data modeling, solution design, code reviews, and technical discussions.

Must Have

  • 4+ years of professional experience in Data Engineering, ETL, or Data Integration.
  • Strong hands-on experience developing ETL/ELT pipelines.
  • Good programming experience with Python.
  • Hands-on experience with Apache Spark and distributed data processing.
  • Experience working with Apache Kafka or similar event-streaming technologies.
  • Strong SQL skills, including complex queries, joins, aggregations, performance optimization, and working with large datasets.
  • Good understanding of relational databases, data warehouses, and data modeling concepts.
  • Experience troubleshooting and optimizing production data pipelines.
  • Strong analytical and problem-solving skills.

Nice to have

  • Experience with Java.
  • Experience with Apache NiFi, including the development and management of data flows.
  • Experience with cloud data platforms such as AWS, Azure, or GCP.
  • Experience with orchestration tools such as Apache Airflow or similar technologies.

What Would Make Someone Excellent in This Role

  • Strong hands-on experience building and optimizing scalable ETL/ELT pipelines.
  • Advanced proficiency in Python, SQL, and Apache Spark for large-scale data processing.
  • Practical experience developing real-time data pipelines using Apache Kafka.
  • Strong understanding of data modeling, data warehousing, and distributed systems.
  • Proven ability to troubleshoot complex data pipeline issues and optimize performance in production environments.
  • Experience with Apache NiFi, Apache Airflow, and cloud data platforms (AWS, Azure, or GCP).
  • Excellent problem-solving skills, attention to data quality, and the ability to translate business requirements into reliable technical solutions.
  • Strong communication and collaboration skills when working with cross-functional technical and business teams.

We will be progressing shortlisted candidates immediately, as this is a strategic and business-critical hire supporting DataHub Analytics’ data engineering capabilities, regional expansion, and AI-driven growth initiatives.

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