Senior Data Engineer [UAE Based] (London Area)

AI71
London
1 week ago
Applications closed

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Job Title: Senior Data Engineer

Location: Abu Dhabi



Job Summary:


As aSenior Data Engineer, you will be responsible for designing, developing, and maintaining advanced, scalable data systems that power critical business decisions. You will lead the development of robust data pipelines, ensure data quality and governance, and collaborate across cross-functional teams to deliver high-performance data platforms in production environments. This role requires a deep understanding of modern data engineering practices, real-time processing, and cloud-native solutions.


Key Responsibilities:


Data Pipeline Development & Management:

  • Design, implement, and maintainscalable and reliable data pipelinesto ingest, transform, and load structured, unstructured, and real-time data feeds from diverse sources.
  • Manage data pipelines foranalytics and operational use, ensuring data integrity, timeliness, and accuracy across systems.
  • Implementdata quality tools and validation frameworkswithin transformation pipelines.

Data Processing & Optimization:

  • Build efficient, high-performance systems by leveraging techniques likedata denormalization,partitioning,caching, andparallel processing.
  • Develop stream-processing applications usingApache Kafkaand optimize performance forlarge-scale datasets.
  • Enabledata enrichmentandcorrelationacross primary, secondary, and tertiary sources.

Cloud, Infrastructure, and Platform Engineering:

  • Develop and deploy data workflows onAWS or GCP, using services such as S3, Redshift, Pub/Sub, or BigQuery.
  • Containerize data processing tasks usingDocker, orchestrate withKubernetes, and ensure production-grade deployment.
  • Collaborate with platform teams to ensure scalability, resilience, and observability of data pipelines.

Database Engineering:

  • Write and optimize complexSQL queriesonrelational(Redshift, PostgreSQL) andNoSQL(MongoDB) databases.
  • Work withELK stack(Elasticsearch, Logstash, Kibana) for search, logging, and real-time analytics.
  • SupportLakehouse architecturesand hybrid data storage models for unified access and processing.

Data Governance & Stewardship:

  • Implement robustdata governance,access control, andstewardshippolicies aligned with compliance and security best practices.
  • Establish metadata management, data lineage, and auditability across pipelines and environments.

Machine Learning & Advanced Analytics Enablement:

  • Collaborate with data scientists to prepare and serve features for ML models.
  • Maintain awareness of ML pipeline integration and ensure data readiness for experimentation and deployment.

Documentation & Continuous Improvement:

  • Maintain thorough documentation includingtechnical specifications,data flow diagrams, andoperational procedures.
  • Continuously evaluate and improve the data engineering stack by adopting new technologies and automation strategies.


Required Skills & Qualifications:

  • 8+ yearsof experience in data engineering within a production environment.
  • Advanced knowledge ofPythonandLinux shell scriptingfor data manipulation and automation.
  • Strong expertise inSQL/NoSQL databasessuch as PostgreSQL and MongoDB.
  • Experience buildingstream processing systems using Apache Kafka.
  • Proficiency withDockerandKubernetesin deploying containerized data workflows.
  • Good understanding ofcloud services(AWS or Azure).
  • Hands-on experience withELK stack(Elasticsearch, Logstash, Kibana) for scalable search and logging.
  • Familiarity withAI modelssupporting data management.
  • Experience working withLakehouse systems,data denormalization, anddata labelingpractices.


Preferred Qualifications:

  • Working knowledge ofdata quality tools,lineage tracking, anddata observabilitysolutions.
  • Experience indata correlation, enrichment from external sources, and managingdata integrity at scale.
  • Understanding ofdata governance frameworksand enterprisecompliance protocols.
  • Exposure to CI/CD pipelines for data deployments and infrastructure-as-code.


Education & Experience:

  • Bachelor’s or Master’s degree inComputer Science,Engineering,Data Science, or a related field.
  • Demonstrated success in designing, scaling, and operating data systems incloud-nativeanddistributed environments.
  • Proven ability to work collaboratively with cross-functional teams including product managers, data scientists, and DevOps.

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