About the job 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 & ExperienceMinimum 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)