Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS)
Not Disclosed•Full-TimeOn-site
location_on9, East 45th Street, Midtown, Manhattan Community Board 5, Manhattan, New York County, New York, 10017, United States
About the Team
The Scientific Computing and Data team at the Icahn School of Medicine at Mount Sinai partners with scientists and clinicians to accelerate scientific discovery. Our expert team of 20+ PhD/MD computational scientists, biomedical informaticists, and computer scientists works to effectively and efficiently utilize high-performance resources for translational science.
The team supports the AI-Ready.Mount Sinai (AIR.MS) platform, a cloud-based, high-performance SAP HANA data platform. AIR.MS ingests OMOP-formatted EHR data from the Mount Sinai Data Warehouse and integrates raw datasets from radiology, genomics, and pathology. It is tightly coupled with Minerva, a high-performance computer offering over 21 petaflops of raw computational power, enabling researchers to access data through direct database access, AI agents, cohort query tools, and the Minerva supercomputer.
Work location
Work model: On-site
9, East 45th Street, Midtown, Manhattan Community Board 5, Manhattan, New York County, New York, 10017, United States
New York, New York
Key Responsibilities
- check_circleDevelop and promote standards, design patterns, and DevOps best practices for pipelines and warehouse maintenance
- check_circleMentor junior engineers in data warehousing, data engineering skills, and operational support
- check_circleDesign, build, and maintain data management processes for loading flat files and JSON data
- check_circleLead design sessions, code walkthroughs, peer reviews, and produce technical documentation
- check_circleTune database objects, stored procedures, and pipelines to optimize performance and minimize costs
- check_circleCollaborate with DBAs on backups, performance tuning, statistics maintenance, and patching
- check_circleIdentify improvements in procedures, technology, compliance, and data privacy/security
- check_circleLead technical efforts for integrating multi-modal clinical data into the AIR.MS data warehouse
- check_circleEnsure patient privacy and data security in compliance with HIPAA, IRB, and cybersecurity policies
- check_circleDesign databases and pipelines balancing functionality, performance, cost, and development time
- check_circleDesign, build, test, and maintain data pipelines to extract, transform, and integrate multi-modal data
- check_circleMonitor database and pipeline operations, lead troubleshooting, and provide on-call support
Requirements
- verifiedBachelors degree in a technical discipline
- verifiedMasters degree preferred
- verified12-15 years preferred of related experience
- verified7 years of experience designing, developing, and maintaining relational databases, data pipelines, and dimensional/OLAP warehouses
- verifiedExpert knowledge of data warehousing: 3NF & dimensional modeling, change data capture, incremental loads, data lineage, source-to-target mappings
- verifiedExperience working with healthcare data
- verifiedExpert-level experience with SQL, indexing, stored procedures, UDFs, sequences, dynamic SQL, data transformation tools, job orchestration tools
- verifiedExperience with DevOps/SDLC best practices; Agile (Scrum, Kanban) with JIRA and Confluence; version control with git
- verifiedExperience with database administration: configuration, performance tuning, partitioning, materialized views, permissions, backups & restorations
- verifiedKnowledge of Hadoop, Spark, Kafka and other big data technology stacks and streaming tools
- verifiedPreferred experience with healthcare data (EHR, billing/claims, cost accounting), Epic Clarity/Caboodle, data models (OMOP, i2b2, PCORnet)
- verifiedKnowledge of SAP HANA technology stack and MySQL
Nice to Have
Masters degree in a technical discipline. 12-15 years of related experience. Experience with healthcare data (EHR, billing/claims, cost accounting), Epic Clarity/Caboodle, and data models (OMOP, i2b2, PCORnet). Knowledge of Hadoop, Spark, Kafka, and other big data technology stacks and streaming tools.
Similar Job Opportunities
Skills, education and keywords
Skills: Sap Hana, MYSQL, SQL, 3NF, Dimensional Modeling, Fact Table Types, SCDS, Change Data Capture, Incremental Loads, Data Lineage.
Education: Bachelor's degree in a technical discipline required; Master's degree preferred.
Frequently asked questions about Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System
What does a Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System do?expand_more
A Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System is responsible for the following: Develop and promote standards, design patterns, and DevOps best practices for pipelines and warehouse maintenance; Mentor junior engineers in data warehousing, data engineering skills, and operational support; Design, build, and maintain data management processes for loading flat files and JSON data; and Lead design sessions, code walkthroughs, peer reviews, and produce technical documentation.
What are the requirements for this Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) role?expand_more
To qualify for the Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System position, applicants should have: Bachelors degree in a technical discipline; Masters degree preferred; 12-15 years preferred of related experience; 7 years of experience designing, developing, and maintaining relational databases, data pipelines, and dimensional/OLAP warehouses; Expert knowledge of data warehousing: 3NF & dimensional modeling, change data capture, incremental loads, data lineage, source-to-target mappings; and Experience working with healthcare data.
Where is the Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) role at Mount Sinai Health System located?expand_more
Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System is based in 9, East 45th Street, Midtown, Manhattan Community Board 5, Manhattan, New York County, New York, 10017, United States. This is a on-site role.
Is this Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) job remote, hybrid, or on-site?expand_more
Mount Sinai Health System has listed this Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) role as on-site.
How much experience is required for this Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) role?expand_more
Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System typically requires 12–15 years of relevant experience at the lead level.
What skills do you need for the Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) role at Mount Sinai Health System?expand_more
Key skills for Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System include Sap Hana; MYSQL; SQL; 3NF; Dimensional Modeling; Fact Table Types; SCDS; and Change Data Capture.
What education is required for Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System?expand_more
Educational requirements for this role: Bachelor's degree in a technical discipline required; and Master's degree preferred.
What category does the Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) role belong to?expand_more
Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS) at Mount Sinai Health System is part of the it job category on Recrutus.