
Data Engineer
2 weeks ago
As a Lead Data Engineer, you will play a leading role in designing, building, and optimizing the client's data infrastructure, ensuring that it supports the bank's advanced analytics needs.
Your main responsibilities will include:
- Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data.
- Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch.
- Collaborate with data engineers, data scientists, and other stakeholders to understand requirements and translate them into technical specifications and solutions.
- Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques.
- Optimize data engineering workflows for containerized deployment and efficient resource utilization.
**Requirements**:
- Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related field.
- At least 10 years of 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, Ranger, etc)
- Experience with containerization platforms such as OpenShift 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 DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
- Experience with Grafana, Prometheus, Splunk will be an added benefit
- Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges.
**Job Types**: Full-time, Contract
Contract length: 24 months
Pay: $6,000.00 - $8,000.00 per month
**Benefits**:
- Health insurance
- Professional development
Schedule:
- Day shift
Work Location: In person
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