Data Engineer (AWS, Databricks)
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Summary
Operations-focused data engineer at NTT Singapore who monitors, tunes, and maintains production data pipelines on AWS and Databricks — handling Spark performance optimization, incident response, disaster recovery, and access control. Core stack includes Databricks, Apache Spark, AWS, IDMC, Tableau, Oracle, and SageMaker.
Role and Responsibilities
Operational Responsibilities
- Monitor and maintain production data pipelines to ensure 99.9% uptime and optimal performance
- Implement comprehensive logging, alerting, and monitoring systems using Application monitoring tools
- Perform regular health checks performance, job execution times, and resource utilization to identify and resolve bottlenecks proactively
- Manage incident response procedures for pipeline failures, including root cause analysis, resolution, and post-incident reviews
- Establish and maintain disaster recovery procedures and backup strategies for critical data assets within the Databricks environment
- Conduct regular performance tuning of Spark jobs and Databricks cluster configurations to optimize cost and execution efficiency
- Maintain comprehensive documentation for operational procedures, runbooks, and troubleshooting guides
- Coordinate scheduled maintenance windows and system upgrades with minimal business impact
- Manage user access controls, workspace configurations, and security policies within Application environments
Requirements / Qualifications
Education & Experience
- Degree in Computer Science or Computer Engineering
- Minimum 5 years working experience in system operations compliance and management areas
- Project hands-on experience specifically with AWS platform (primary requirement)
- Project experience in cloud operations or cloud architecture
- Must be cloud certified (AWS)
Core Technical Skills
- Proficiency in Databricks platform, including workspace management, cluster configuration, and job orchestration
- Strong expertise in Apache Spark within Databricks environment, including Spark SQL, DataFrames, and RDDs
- Good in-depth understanding of data warehouse concepts, data profiling, data verification and advanced analytics techniques
- Strong knowledge of monitoring, incident management, and cloud cost control
Technology Stack Experience
- Databricks
- AWS cloud services and architecture
- IDMC (Informatica Data Management Cloud)
- Tableau for data visualization
- Oracle Database management
- ML Ops practices within Databricks environment
- STATA for statistical analysis is advantage
- Amazon SageMaker integration with Databricks
- DataRobot platform integration
Soft Skills & Stakeholder Management
- Good interpersonal skills with the ability to work with different groups of stakeholders
- Strong problem-solving skills and ability to work independently in a fast-paced environment with minimal supervision
- Excellent communication skills for technical documentation and cross team collaboration
Desirable Requirements
- AWS certification (Associate or Professional level) - highly preferred
- Exposure to hospital information/clinical systems is an added advantage
- Understanding of DevOps practices and CI/CD pipelines for Databricks based data engineering projects