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Experience implementing data platform engineering practices that improve developer productivity, automation, reuse, and delivery velocity.
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Demonstrated success modernizing enterprise-scale platforms using DataOps, CI/CD, Infrastructure-as-Code, automated testing, data observability, and reliability engineering principles. - policy-as-code, DataGovOps, data contracts
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Bachelor’s degree required; advanced degree preferred in Computer Science, Data Engineering, Information Systems, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.
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10+ years of progressive experience delivering enterprise data platforms, data products, and analytics at scale, including translating business needs into trusted, reusable data assets with measurable business impact; life sciences/healthcare experience strongly preferred.
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5+ years building and leading high-performing data and analytics teams, including hiring, coaching, performance management, and developing technical leaders, with experience managing significant operating investment and extended/vendor teams.
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Deep expertise in modern data architecture and platforms (e.g., lakehouse, data warehouse, and streaming) and hands-on fluency with leading cloud and data technologies (e.g., AWS, Azure, GCP, Databricks, Snowflake) and modern data pipelines/ELT.
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Proven track record standing up a data-as-a-product operating model—data product management, semantic layers, master data management, and self-service analytics—and delivering core analytics that drive decisions.
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Strong command of data governance, data quality, cataloging, lineage, and metadata management, with the ability to embed controls by design in a regulated environment.
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Working knowledge of data standards, privacy regulations, and governance expectations in regulated environments, and the ability to partner effectively with Security, Privacy, Legal, and Compliance.
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Demonstrated ability to prioritize a portfolio, manage investment across the data product lifecycle, and drive adoption and value realization through clear OKRs/KPIs and stakeholder alignment.
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Exceptional written and verbal communication, with the ability to explain complex technical concepts to diverse audiences and influence decisions from the executive level to delivery teams.
