Data Engineer- DevOps

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)

**PERSOLKELLY Singapore Pte Ltd - RCB No. 200007268E - EA License No. 01C4394**
**R1547247 (Jyothi Chandrakanth Kamath)
**About our client**:
Our client is reputed Bank.

**Working hours: Monday - Friday (8.30AM to 6.00PM / 9.00AM to 6.30PM)**

**Salary : Up to S$ 13500/month.**

**Duration: 12 months contract**

**Working locations: Central.
**About the Client**

Our client is one of the reputed MNC firms in Singapore
- 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 OpenShift Container Platform (OCP) using containerization and orchestration techniques
- Optimize data engineering workflows for containerized deployment and efficient resource utilization
- Collaborate with DevOps 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 DevOps
- 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

**Skills/Requirement**

**Must have Skills**:

- Must have Skills:

- 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 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 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