Senior Principal Data Engineer
New
J
JobgetherData engineering
Based in the United StatesFull-TimePrincipal
SalaryAnnual base salary range of $150,900–$195,900
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Job Details
- Experience
- 7+ years of experience in Data Engineering, Software Engineering, Data Platform Engineering, or a closely related field.
- Required Skills
- AWSDockerPythonSQLGitKubernetesAzureCI/CDRESTful APIsDatabricks
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical discipline; a Master’s degree is preferred.
- 7+ years of experience in Data Engineering, Software Engineering, Data Platform Engineering, or a closely related field.
- Extensive experience designing and implementing enterprise-scale cloud data platforms and data architectures.
- Expert-level programming skills in Python and SQL.
- Strong expertise in conceptual, logical, and physical data modeling.
- Hands-on experience with Databricks, Azure, AWS, Docker, Kubernetes, Git, REST APIs, and CI/CD environments.
- Strong understanding of software architecture, design patterns, distributed systems, and secure data platform design.
- Experience establishing engineering standards, governance practices, reusable frameworks, and technical roadmaps.
- Ability to lead complex technical initiatives through influence and collaboration rather than direct people management.
- Experience mentoring experienced engineers and collaborating across Product, Data Science, Analytics, Governance, Architecture, and Infrastructure functions.
- Preferred experience in pharmaceutical, biotechnology, healthcare, or another regulated industry.
- Preferred experience with Databricks Unity Catalog, enterprise data governance, metadata management, data lineage, observability, Infrastructure as Code, or Generative AI applied to software or data engineering.
Responsibilities
- Design and evolve enterprise-scale data platform architectures for analytical, operational, and AI workloads.
- Define reusable engineering frameworks, reference architectures, design patterns, and technical standards.
- Establish platform strategies and influence technical direction across business domains and engineering teams.
- Lead architecture reviews, technical design sessions, and engineering governance for complex initiatives.
- Design ETL/ELT frameworks, enterprise data pipelines, and conceptual, logical, and physical data models.
- Develop metadata-driven data integration frameworks and standards for modeling, metadata, lineage, and performance.
- Evaluate AI coding assistants and develop AI-powered engineering accelerators.
- Design secure, governed data platforms with access controls, observability, metadata, and lineage.
- Mentor senior and principal engineers and collaborate with Product, Data Science, Analytics, Governance, Architecture, and Infrastructure teams.
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