Lead Data Warehouse Engineer - Artificial Intelligence-Ready Mount Sinai (AIR.MS)

Mount Sinai Medical Center; New York (NY); On-site; USD 145,200 - 217,875; Full time

Job summary

Mount Sinai Medical Center is seeking a Lead Data Warehouse Engineer to integrate multi-modal clinical data into the AIR.MS data warehouse. This senior role involves designing data pipelines, mentoring engineers, and ensuring compliance with privacy regulations. Candidates should possess a Bachelor’s degree and extensive experience in data warehousing. The salary range for this position is $145,200 to $217,875 annually, depending on experience and education.

Qualifications

• 12-15 years of related experience preferred.
• 7 years of experience in designing, developing, and maintaining databases.

Responsibilities

• Design databases and pipelines balancing functionality and performance.
• Maintain data pipelines to capture and transform data.
• Mentor junior engineers in data practices.
• Ensure compliance with patient privacy regulations.

Skills

Data warehousing expertise

Relational databases

SQL

Data integration

DevOps practices

Customer service skills

Critical thinking

Multitasking

Education

Bachelor's degree in a technical discipline

Master’s degree preferred

Tools

SAP HANA

MySQL

JIRA

Confluence

Hadoop

Spark

Kafka

Job description

Description

The Scientific Computing and Data team at the Icahn School of Medicine at Mount Sinai partners with scientists and clinicians to accelerate scientific discovery. The AI-Ready.MountSinai (AIR.MS) platform contains patient data generated from the clinical care processes at the Mount Sinai Health System. AIR.MS is a cloud‑based, high‑performance SAP HANA data platform with electronic health record (EHR) data in an OMOP data format. It also contains metadata from and links to raw data sets in other modalities, such as radiology, genomics and pathology. Researchers can access the AIR.MS data through direct database access, AI agents, cohort query tools and the Minerva high‑performance computer. AIR.MS ingests OHDSI’s Observational Medical Outcomes Partnership (OMOP)‑formatted EHR data from the Mount Sinai Data Warehouse. AIR.MS is integrated with Minerva, a high‑performance computer with >21 petaflops of raw computational power and the raw radiology, genomics and pathology data sets. An expert team of 20+ PhD/MD computational scientists, biomedical informaticists and computer scientists partner with researchers and clinicians to effectively and efficiently utilize these resources for translational science.

The Lead Data Warehouse Engineer is a senior technical specialist responsible for leading the ongoing integration of multi‑modal clinical data into the AIR.MS data warehouse. The Lead Data Warehouse Engineer will assess the state of data integration, identify opportunities for data integration based on researcher priorities, develop a plan to integrate metadata and data, and execute on the data integration. The incumbent will work collaboratively with other members of the AIR.MS data platform and Mount Sinai Data Warehouse teams to lead technical efforts for the integration of multi‑modal data sets resulting in expanded AIR.MS functionality. The AIR.MS data warehouse is built on the SAP HANA technology stack and MSDW is built on MySQL.

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

• Bachelor's degree in a technical discipline; Master’s 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.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

Compensation

The Mount Sinai Health System (MSHS) provides salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements. The salary range for the role is $145,200 – $217,875 annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.