Senior OLAP Performance Engineer

Merative is a company that transforms healthcare data into actionable insights through analytics and data solutions. They are seeking a Senior OLAP Performance Engineer who will be responsible for optimizing the performance and scalability of the OLAP and cube-based analytics platform, focusing on query tuning and performance improvements.

Responsibilities:

• Continuously improve and maintain the performance of the OLAP/cube analytics platform through hands-on query tuning, cube optimization, and dashboard performance improvements
• Design, prototype, refine, and optimize cubes and semantic-layer structures, including hierarchies, partitions, aggregates, caches, and precomputed measures
• Proactively analyze and resolve performance bottlenecks by evaluating query execution patterns, underlying data structures, and resource utilization
• Assess vendor roadmaps by evaluating new platform capabilities, testing pre‑release features, and advising on opportunities to enhance performance and scalability
• Serve as the primary troubleshooter for slow-running queries, dashboard inefficiencies, concurrency issues, and refresh delays
• Optimize how BI/reporting tools connect to and query the OLAP layer by improving semantic structures and query paths
• Ensure the OLAP platform scales effectively in a multi-tenant environment, preserving tenant isolation, predictable performance, and cost efficiency as both user volume and data size grow
• Implement and maintain monitoring for cube performance, including query execution patterns, refresh behavior, caching efficiency, and overall environment health
• Define baseline performance metrics to detect degradations, conducting release-over-release performance analysis for platform upgrades, feature enhancements, and cross-team validation efforts
• Document performance findings, tuning techniques, and troubleshooting approaches to support knowledge sharing and consistent problem-solving
• Demonstrate strong ownership and a self-starter mindset in identifying improvement opportunities and driving solutions independently
• Guide teams and stakeholders in understanding performance tradeoffs, data modeling decisions, and optimization strategies

Requirements:

• Extensive hands-on experience with OLAP/cube technologies such as Kyvos, SSAS, Essbase, Kylin, or similar platforms
• Expert-level proficiency in MDX with demonstrated ability to diagnose and optimize complex MDX queries
• Strong SQL skills and ability to analyze data structures, lineage, and transformations that impact analytical performance
• Deep experience in multidimensional OLAP cube and semantic-layer design, including hierarchies, partitions, aggregates, caching strategies, and measure calculations
• Proven ability to troubleshoot and tune large-scale analytical workloads, including cube refresh performance and concurrency issues
• Experience with distributed environments such as Spark, Databricks, Hive, or Presto, and columnar storage formats such as Parquet, or ORC
• Hands-on experience in cloud environments (Azure strongly preferred), including VM tuning, ADLS optimization, and observability tooling
• Strong understanding of ETL/ELT pipelines and ability to reshape or precompute data to achieve required performance
• Excellent communication skills with the ability to articulate technical decisions and performance tradeoffs
• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field required
• Experience with healthcare data (claims, eligibility, clinical, or member-level analytics) is preferred but not required
• Master's degree in a related technical or analytics discipline preferred