Data Engineer

2 weeks ago

Singapore Unison Consulting Pte Ltd Full time

**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
- 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
- Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch
- Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration
- Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components
- 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

**Requirements**:

- More than 5 years of experience as a Data Engineer
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline
- Possession of **Quantexa certification as a Data Engineer or Data Architec**t, with proficiency in the tool
- Demonstrated experience as a Data Engineer, utilizing Hadoop, Spark, and data processing technologies in large-scale environments
- Expertise in the Scala programming language and familiarity with functional programming principles
- Prior experience with the **Quantexa tool** is highly desirable
- Comprehensive understanding of Apache Spark architecture, including RDDs, DataFrames, and Spark SQL
- Advanced proficiency in designing and developing data infrastructure utilizing Hadoop, Spark, and associated tools (HDFS, Hive, Pig, etc.)
- Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration via Kubernetes
- Proficiency in programming languages commonly employed in data engineering, including Spark, Python, Scala, or Java
- Knowledge of DevOps methodologies, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
- Experience with Graphana, Prometheus, and Splunk will be considered an added advantage
- Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization techniques
- Experience with distributed computing, parallel processing, and handling large datasets
- Strong problem-solving and analytical capabilities with the capacity to debug and resolve intricate issues
- Familiarity with version control systems (e.g., Git) and collaborative development environments

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