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Data Platform Engineer

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Job Description - Data Platform Engineer

Data Platform Engineer - 12 Month Contract

Key Responsibilities
Platform Engineering & Development
  • Design, implement, and maintain Big Data platforms (e.g., Hadoop, Spark, Kafka) used across the CIB environment.
  • Build robust batch and real-time data ingestion pipelines using tools like Apache NiFi, Airflow, Spark, and Kafka Streams.
  • Maintain and enhance enterprise data lakes and warehouse environments using technologies such as Hive, Delta Lake, and Azure Synapse.
️ Cloud & Hybrid Integration
  • Architect and deploy data platform solutions on Microsoft Azure (Databricks, Azure Data Lake Storage, Synapse Analytics).
  • Build hybrid cloud systems to integrate on-premises and cloud-based data infrastructure.
  • Ensure optimal performance, scalability, and cost-efficiency across cloud workloads.
️ Data Governance, Compliance & Security
  • Ensure platform compliance with data governance and privacy regulations (POPIA, GDPR, BCBS239).
  • Implement robust security controls across infrastructure including encryption, access controls, and audit logging.
  • Work closely with data stewards and governance teams to integrate metadata management and data cataloging tools.
Automation & DevOps
  • Develop and maintain CI/CD pipelines for automated testing, deployment, and monitoring of data solutions.
  • Automate infrastructure provisioning using tools like Terraform and Azure DevOps.
  • Perform routine system administration, performance tuning, and issue resolution across data platforms.
Monitoring & Support
  • Implement monitoring solutions (e.g., Prometheus, Grafana, ELK Stack) to ensure system availability and reliability.
  • Provide L2/L3 support for production data environments, managing incidents and service requests effectively.
Stakeholder Engagement
  • Collaborate with cross-functional teams including data scientists, analysts, developers, and compliance teams.
  • Translate business and analytical requirements into scalable platform solutions.
  • Participate in Agile sprints and architecture design reviews.
Qualifications & Experience
Minimum Requirements
  • Bachelors degree in Computer Science, Information Systems, Engineering, or related field.
  • 5+ years of experience in Big Data engineering or platform operations.
  • Experience in enterprise-grade platforms in banking or financial services.
Technical Skills
  • Strong proficiency with Hadoop ecosystem: HDFS, Hive, Spark, Kafka.
  • Expertise in Azure cloud services: Azure Data Factory, Azure Databricks, Azure Data Lake, Synapse Analytics.
  • Solid programming skills in Python, Scala, Java, and SQL.
  • Familiarity with Terraform, Git, Jenkins, Docker, and Kubernetes.
  • Experience with data governance tools such as Apache Atlas or Collibra is advantageous.
Soft Skills
  • Excellent problem-solving and troubleshooting ability.
  • Strong communication and collaboration skills.
  • Ability to work in a fast-paced, high-stakes environment.
Preferred Certifications
  • Microsoft Certified: Azure Data Engineer Associate
  • Cloudera Data Platform Certified Developer
  • Databricks Certified Data Engineer Associate
  • TOGAF or similar architecture frameworks (advantageous)
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