Data Engineer (AWS, Databricks)

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