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Data Engineer

Saal.ai
Abu Dhabi, UAE
Full-time
Mid-Senior
Onsite
Discovered 6 days ago
Data pipeline design and operationBatch and streaming data processingData Lake/Lakehouse architectureDelta Lake or Iceberg (or equivalent)Distributed data architecturesData modeling and OLAP design

Full Job Posting

Role purpose

Design, develop, and maintain scalable data platforms and pipelines for analytics, AI, operational reporting, and data-driven products.

Work with software engineers, solution architects, analysts, data scientists, and business stakeholders to deliver reliable, secure, efficient data solutions.

The role involves modern data engineering technologies, batch and streaming processing, cloud-native platforms, and distributed systems.

Key responsibilities

  • Define and build ingestion frameworks for large-scale structured, semi-structured, unstructured, and streaming data.
  • Design, develop, and maintain scalable batch and streaming pipelines, including workflows using Apache NiFi, Kafka, Spark, Flink, and Airflow.
  • Design data models for analytical and operational workloads.
  • Collaborate with internal product teams and third-party service providers on integrations and platform enhancements.
  • Participate in sprint planning, development, and delivery activities.
  • Deploy and support workloads in cloud and containerized environments.
  • Monitor, troubleshoot, and optimize platform performance and reliability; ensure solutions are scalable, observable, secure, and manageable.

Essential skills and experience

  • Strong experience designing, building, and operating production data pipelines.
  • Experience with Data Lake or Lakehouse architectures, including Delta Lake, Iceberg, or equivalent.
  • Understanding of distributed data architectures, data modeling, OLAP design, and CDC, including tools such as Debezium.
  • Experience with large-scale storage and messaging platforms, including MinIO/S3 and Kafka.
  • Experience integrating enterprise systems through REST APIs, messaging platforms, and event-driven architectures.
  • Proficiency in batch and real-time processing; familiarity with Avro, Parquet, and ORC formats.
  • Strong scripting or programming skills and experience delivering enterprise analytics and reporting platforms.
  • Experience with infrastructure and container deployments; familiarity with Grafana, Prometheus, ELK/OpenSearch, Dynatrace, or equivalent monitoring tools.
  • Experience with Azure Databricks, Azure Data Lake Storage, Azure Event Hubs, and Azure Synapse Analytics.
  • Understanding of data governance, lineage, access controls, and data security; experience in Agile development environments.

Education and experience

  • Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related discipline.
  • Five to eight years of professional experience as a Data Engineer, Big Data Engineer, or Data Platform Engineer.
  • Relevant professional certifications are advantageous.

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