Provide the tools necessary to deliver cutting-edge health care and groundbreaking research. As part of our Information Technology team, you’ll ensure that our medical professionals have access to the latest breakthroughs in technology, and you’ll play a key role in protecting our global patient community.
We’re seeking an experienced Senior Data Engineer to join our team! In this role you will:
- Design and build scalable data pipelines and platforms that integrate complex enterprise and external data sources.
- Develop trusted data products, curated datasets, and reusable data models supporting reporting, analytics, data science, machine learning, and AI.
- Engineer solutions across clinical, operational, financial, research, and administrative healthcare data.
- Advance cloud-based data capabilities using Azure, Databricks, lakehouse architectures, enterprise data warehousing, and ML-ready data.
- Apply modern engineering practices, including automated testing, CI/CD, orchestration, monitoring, observability, and production support.
- Optimize data solutions for performance, scalability, reliability, security, and usability.
- Establish standards and reusable frameworks for data modeling, metadata, governance, data quality, security, and engineering.
- Develop technical architecture, data lineage, data dictionaries, runbooks, and other documentation supporting reliable enterprise data operations.
- Partner across technology and business teams to translate complex requirements into scalable, sustainable data solutions.
- Lead technical design and architecture discussions and help define implementation and operational support approaches for strategic initiatives.
- Mentor engineers through code reviews, technical guidance, workshops, and knowledge sharing.
Partner with leadership to shape engineering standards, platform capabilities, and the long-term data architecture roadmap.
Salary Range: $108,900.00 – $241,500.00 annually
Salary offers are based on a variety of factors including qualifications, experience, and internal equity. The University anticipates offering a salary between the minimum and midpoint of this range.
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5+ years of experience in data engineering, software engineering, backend engineering, analytics engineering, or related technical roles.
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Strong programming experience with Python, including the ability to write clean, modular, maintainable, and production-quality code.
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Solid understanding of data warehousing, ETL/ELT design patterns, dimensional modeling, data lake/lakehouse concepts, and large-scale data processing.
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Experience designing and building data pipelines that ingest, transform, validate, and publish data from multiple source systems.
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Experience working with modern data platforms such as Databricks, Spark, Delta Lake, Snowflake, Microsoft Fabric, or similar technologies.
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Working knowledge of cloud platforms such as Azure, AWS, or GCP. Microsoft Azure experience is especially valuable.
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Experience with orchestration and pipeline execution tools such as Azure Data Factory, Databricks Workflows, Airflow, or similar platforms.
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Experience with production engineering practices such as Git-based development, CI/CD, automated testing, code reviews, logging, monitoring, and release management.
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Experience with machine learning data workflows, feature engineering, feature stores, ML-ready datasets, MLflow, MLOps, or AI/GenAI-supporting data infrastructure including RAG based systems.
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Ability to collaborate effectively with technical and non-technical stakeholders, including architects, analysts, data scientists, product managers, business teams, and application owners.
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Strong written and verbal communication skills, with the ability to explain technical decisions clearly and document solutions for long-term maintainability.
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Bachelor’s degree in computer science, Computer Engineering, Data Engineering, Information Systems, or a related technical field. A master’s degree is a plus.
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MONICA
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SOZIT
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EDGAR
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KATHERINE
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RADU
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JENNA
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SHARON
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Awards & recognition
