Data Engineer (Healthcare Sector)

Position Summary The role involves working on critical projects including the Healthcare Data Analytics Platform modernization and advanced analytics infrastructure supporting machine learning operations. The position holder will be expected to mentor junior team members. Key projects include migrating existing ETL processes from traditional data warehouse systems to Databricks Delta Lake architecture, implementing real-time streaming analytics for clinical monitoring systems. The role requires close collaboration with infrastructure teams, compliance officers. Role and 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 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, Data Frames, 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 Data Robot 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