Data Platform Engineer

About the position

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)

Place of work