Build our future together:
Global Development is embarking on a Digital Transformation project incorporating AI, machine learning, and automation to help us reduce cycle times, improve quality allowing us to focus on more meaningful work. We focus on developing and improving data pipelines, infrastructure, architecture, and analytic tools to allow resources to fuel our transformation. Working with a team of engineers, analysts, and scientists, you will contribute to modernizing our clinical data infrastructure. This highly visible role will be a technical and strategic liaison between the transformation projects and IT.
A key responsibility will be developing and optimizing schema and data models for clinical data. We ensure that those products are standard compliant and interoperable with other platforms and data sources. This role will also contribute to data governance strategy and to the development and management of tools improving and monitoring data quality. The data engineer will also develop processes to automate routine workflows. The engineer will also provide technical leadership and mentorship and will stay current with innovations in data engineering so that they may be evaluated for implementation.
This position offers the opportunity to contribute to a fast-growing, science-driven organization making a meaningful difference to patients worldwide.
When & where:
This can be a remote position in the US or on-site position at our Armonk, NY or Warren, NJ offices.
Discover your role:
• Work with a cross-functional team to optimize and implement our data strategy with a focus on optimization for digital transformation and the use of AI/ML
• Design and document end-to-end data architectures that support diverse analytic, operational, and research needs.
• Facilitate the implementation of a modern data platform (e.g. Snowflake, Databricks, etc.)
• Identify opportunities and implement solutions to increase data interoperability and standardization among systems and across other business units.
• Develop and implement pipelines to monitor and improve both internal and external (i.e., from CRO partners) data quality.
• Work with informatics and AI engineers optimizing the utility of data for their respective pipelines.
• Monitor and optimize the performance of data architectures and platforms.
• Develop or implement critical metrics to measure the impact of the overall data strategy.
• Stay up to date with the latest advances in the field and, as appropriate, evaluate them for adoption
This role requires:
An advanced degree in computer science, statistics, biomedical informatics, or a related field is preferred (PhD + 2 years of experience or an MS + 4 years of relevant experience). A minimum of 5 years’ experience developing and leading the implementation of data engineering solutions, including accountability for the success of the implementation, in life sciences or healthcare
• Demonstrated expertise in designing and maintaining infrastructure and architecture for clinical or biomedical data in a healthcare or life sciences setting.
• Expertise in modern data platforms (e.g., Snowflake, Redshift, BigQuery, Databricks) and programming languages such as Python, SQL, R, etc.
• Maintain and manage code repositories (e.g Bitbucket) ensuring clean, well-documented code with proper version control.
• Proficiency in cloud architecture (e.g. AWS, Azure, GCP) and DevOps practices. Recognized certifications are a plus.
• Experience building, scaling, and maintaining pipelines for structured and unstructured data. Ability to integrate pipelines across the enterprise is essential.
• Deep understanding of regulatory frameworks (HIPAA, GDPR, 21 CFR Part 11) and clinical data standards (CDISC, HL7, FHIR).
• Knowledge of machine learning pipelines and integration with clinical data platforms.
• May require travel up to 20%.
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