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Job Summary:
Mount Sinai Morningside is seeking a Lead Data Warehouse Engineer for their Scientific Computing and Data team at the Icahn School of Medicine. This role is responsible for leading the integration of multi-modal clinical data into the AIR.MS data warehouse and collaborating with teams to enhance functionality and efficiency.
Responsibilities:
• Design databases and pipelines that balance functionality, performance, cost, and development time; evaluate technical options with the product manager.
• Design, build, test, and maintain data pipelines that extract/capture data from source systems, transform and augment those data, and integrate it into a multi-modal data repository.
• Serve as a team leader; contribute to project planning, work breakdown, dependency sequencing, and release management.
• Develop and promote standards, conventions, design patterns, DevOps/SDLC best practices, and operational procedures for pipelines and warehouse maintenance.
• Mentor junior engineers in data warehousing, data engineering skills, and operational support.
• Design, build, and maintain data management processes, including loading flat files (csv, tsv, pipe-delimited, JSON).
• Lead design sessions, code walkthroughs, peer reviews, and produce technical documentation.
• Tune database objects, stored procedures, and pipelines to optimize performance and minimize compute and storage costs.
• Monitor database and pipeline operations; lead troubleshooting and remediation of failures; provide occasional after-hours on-call support.
• Collaborate with DBAs and system administrators on backups, performance tuning, statistics/index maintenance, and patching.
• Provide high-quality customer service to researchers, clinicians, and internal partners; maintain a science‑driven, customer-focused approach.
• Ensure patient privacy and data security in compliance with IRB & cybersecurity policies, HIPAA, 42 CFR Part 2, NYS Article 27-F, and other regulations.
• Stay current with emerging technologies to improve capabilities, efficiency, quality, or cost.
• Identify improvements in procedures, technology, compliance, and data privacy/security.
• Periodically assist DBAs with user provisioning, backups, restorations, capacity planning, and performance monitoring.
• Perform related duties as assigned.
Qualifications:
Required:
• Bachelors degree in a technical discipline; Masters degree preferred
• 12-15 years preferred of related experience, including 7 years of experience designing, developing, and maintaining relational databases, data pipelines, and dimensional/OLAP warehouses.
Preferred:
• Expert knowledge of data warehousing: 3NF & dimensional modeling (fact table types, SCDs), change data capture, incremental loads, data lineage, source-to-target mappings, pattern-based & parameter-driven development.
• Experience working with healthcare data
• Expert-level experience with data engineering technologies: SQL, indexing, stored procedures, UDFs, sequences, dynamic SQL, data transformation tools, job orchestration tools for data processing.
• Experience with DevOps/SDLC best practices; Agile (Scrum, Kanban) with JIRA and Confluence; version control with git.
• Strong communication and customer service skills for working with researchers, clinicians, administrators, and IT staff.
• Excellent critical thinking, problem-solving, multitasking, and collaboration skills; ability to work independently in a fast-paced environment.
• Preferred experience with healthcare data (EHR, billing/claims, cost accounting), Epic Clarity/Caboodle, data models (OMOP, i2b2, PCORnet).
• Experience with database administration: configuration, performance tuning, partitioning, materialized views, permissions, backups & restorations.
• Knowledge of Hadoop, Spark, Kafka and other big data technology stacks and streaming tools.
Company:
At Mount Sinai Morningside, we offer exceptional clinical care and research within the comfort of a neighborhood hospital known for compassion and sensitivity. Founded in 1846, the company is headquartered in New York, US, , with a team of 1001-5000 employees. The company is currently Late Stage.