Your Profile

We are seeking a skilled and motivated Data Engineer with expertise in Hadoop, Spark, Open Shift Container Platform (OCP), and Dev Ops practices. As a Data Engineer, you will be responsible for designing, developing, and maintaining efficient data pipelines, processing large-scale datasets. Your expertise in Hadoop, Spark, OCP, and Dev Ops will be crucial in ensuring the availability, scalability, and reliability of our ML Solutions.
Responsibilities:

• Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives
  
• Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions
  
• Ensure data quality and integrity throughout the data processing lifecycle
  
• Design and deploy data engineering solutions on Open Shift Container Platform (OCP) using containerization and orchestration techniques
  
• Optimize data engineering workflows for containerized deployment and efficient resource utilization
  
• Collaborate with Dev Ops teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability
  
• Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance
  
• Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements
  
• Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure
  
• Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference
  
• Stay updated with emerging technologies, industry trends, and best practices in data engineering and Dev Ops
  
• Provide technical leadership, mentorship, and guidance to junior team members to foster a culture of continuous learning and innovation to the continuous improvement of the analytics capabilities within the bank

Requirements

Requirements:

• Bachelor's degree in Computer Science, Information Technology, or a related field
  
• Proven experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments
  

• Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)
  
• Experience with containerization platforms such as Open Shift Container Platform (OCP) and container orchestration using Kubernetes
  
• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java
  
• Knowledge of Dev Ops practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, Bit Bucket)
  
• Experience with Graphana, Prometheus, Splunk will be an added benefit
  
• Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges
  
• Excellent collaboration and communication skills to work effectively with cross-functional teams
  
• Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment
  
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus