Data Operations Engineer (1 Year Contract)

Job Overview You will be deployed to our client who is a leading government technology agency driving digital transformation and innovation in the healthcare sector. Seeking a L3 Data Operations Engineer for the data engineering team to accelerate the implementation andoperationalization of our enterprise data platform built on Databricks. The successful candidate will be responsible for leading the migration of legacy data pipelines to Databricks, establishing operational excellence frameworks,and ensuring seamless integration with existing healthcare information systems and clinical data workflows. 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 • 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) • 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 • 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 • 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 • Exposure to hospital information/clinical systems is an added advantage • Understanding of DevOps practices and CI/CD pipelines for Databricks-based data engineering projects If you are interested in this role and would like to discuss the opportunity further please click apply now or email Chew Kai-Xinn at kaixinnchew@morganmckinley.com for more information. Only shortlisted candidates will be responded to, therefore if you do not receive a reply within 14 days please accept this as notification that you have not been shortlisted. Morgan McKinley Talent Solutions Morgan McKinley Pte Ltd EA Licence No: 11C5502 EAP Registration No: R2196712 EAP Name: Chew Kai-Xinn