Envista Principal Data Engineer

Job Description:

JOB SUMMARY:

The Principal Data Engineer designs, builds, and governs secure, scalable, and high-performing enterprise data solutions that support advanced analytics, business intelligence, and operational decision-making. This role serves as a technical authority across the project lifecycle, translating business needs into sustainable architectures, establishing standards, and enabling reliable access to high-quality data across cloud, on-premises, and hybrid environments. The position balances innovation with security, compliance, interoperability, and long-term platform sustainability while influencing technical and business stakeholders across teams.
PRIMARY DUTIES AND RESPONSIBILITIES:

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Design, build, and optimize scalable data pipelines for structured and unstructured data, including reliable ETL/ELT processes that move data from multiple sources into data warehouses and data lakes.

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Develop and maintain enterprise data models, integration frameworks, storage solutions, and architectural patterns across cloud, on-premises, and hybrid environments.

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Define and maintain data solution architecture and governance frameworks that align technical decisions with long-term business objectives and enterprise goals.

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Provide technical leadership throughout the project lifecycle, including architecture reviews, solution validation, performance tuning, deployment strategy, and resolution of complex technical issues.

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Establish and promote architecture principles, engineering standards, and best practices across development teams to improve scalability, reliability, interoperability, and consistency.

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Implement data quality, lineage, metadata management, backup, accessibility, security, and governance practices across diverse systems and global data environments.

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Partner with IT security and compliance teams to embed appropriate controls and support adherence to applicable regulatory and internal requirements, including GDPR, HIPAA, and SOX.

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Collaborate with business stakeholders, data scientists, analysts, BI teams, and IT partners to translate business needs into clear technical designs and accessible data solutions.

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Clean, transform, and organize raw data into usable formats and create analytical tools or programs that support analysis, reporting, and informed decision-making.

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Evaluate and optimize existing data systems to improve performance, reliability, speed, and maintainability while managing complexity across multi-cloud and hybrid platforms.

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Evaluate emerging technologies, make informed recommendations under uncertainty, and apply innovative solutions that balance business value with security, compliance, and operational risk.

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Build strong cross-functional relationships, communicate complex technical concepts clearly to technical and non-technical audiences, and maintain stakeholder alignment throughout delivery

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Adapt technical approaches and priorities as technologies and business needs evolve while sustaining data quality, platform stability, and delivery commitments.

Job Requirements:
MINIMUM REQUIREMENTS:

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Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field –or- equivalent experience.

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10+ years of experience in data engineering.

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Expertise in designing scalable data solutions using modern architecture patterns, including microservices, event-driven architecture, and API-first design.

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Proficiency with ETL/ELT tools, data warehousing, big data technologies, and database systems.

- Proficiency in SQL and Python

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Strong knowledge of enterprise data architecture, data modeling, integration frameworks, and data governance practices.

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Experience with cloud platforms such as Azure, AWS, or GCP and data services such as Snowflake or Databricks.

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Experience designing and supporting solutions across cloud, on-premises, or hybrid environments.

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