Full-Time
Dubai, Hybrid, Remote
Posted 3 months ago

What you will do?

  • Design end-to-end data solutions, including solution architecture, data modeling, and data flow diagrams, to address complex business requirements.
  • Design, develop, and maintain scalable data pipeline architecture to support the company’s and clients’ data processing needs.
  • Implement best practices for data ingestion, storage, and processing to ensure data integrity, reliability, and security.
  • Architect and implement Big Data processing workflows to handle large volumes of data with high throughput and low latency, ensuring timely and accurate data delivery.
  • Drive the adoption of data engineering best practices and standards across the organization, including data governance, data security, and data quality.
  • Lead and mentor junior team members, providing guidance on best practices and technical solutions.
  • Maintains consistent communication with the Project Team Lead and Project Manager, providing clear updates on task status and promptly escalating any issues or potential delays

Good to have:

  • Design and develop real-time streaming data pipelines using technologies such as Apache Kafka, Apache Pulsar, or cloud-native streaming services (e.g., AWS Kinesis, Google Cloud Pub/Sub).
  • Lead data architecture reviews and provide recommendations for optimizing performance, scalability, and cost efficiency.
  • Collaborate with data scientists and analysts to understand data requirements and provide technical expertise in data modeling and analytics.

What we are looking for?

  • Proficiency in designing, building, and maintaining scalable ETL data processing systems using Python, Java, Scala, or similar programming languages.
  • Expertise in SQL – Demonstrate a strong grip on SQL to process and analyze various forms of data.
  • Experience working with Cloud Deployment Environments, preferably GCP, Azure or AWS.
  • Experience in creating and managing CI/CD pipelines using Azure DevOps, Jenkins, GoCD, or similar technologies.
  • Proficiency in orchestration tools like Apache Airflow, Azure Data Factory, AWS Data Pipelines, or similar.
  • Familiarity with version control systems like GitHub and CI/CD concepts.
  • Understanding of Data Modeling and Data Warehousing techniques, including star schema or raw data vault.
  • Experience working with large-scale data sets, including structured and unstructured data formats like Parquet, Avro, JSON, etc.

Good to have:

  • Knowledge of big data processing technologies such as Hadoop, Apache HBase, Apache Hive, or similar.
  • Experienced with designing and implementing Data Governance policies covering Data Accessibility, Security, Management, Quality etc.

Job Features

Job Category

Data Engineer

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