Envista Principal Data Engineer (Remote)

Envista Holdings Corporation

5d•$159,500 - $194,900•Remote

About The Position

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.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field –or- equivalent experience.
10+ years of experience in data engineering.
Expertise in designing scalable data solutions using modern architecture patterns, including microservices, event-driven architecture, and API-first design.
Proficiency with ETL/ELT tools, data warehousing, big data technologies, and database systems.
Proficiency in SQL and Python
Strong knowledge of enterprise data architecture, data modeling, integration frameworks, and data governance practices.
Experience with cloud platforms such as Azure, AWS, or GCP and data services such as Snowflake or Databricks.
Experience designing and supporting solutions across cloud, on-premises, or hybrid environments.
Familiarity with security best practices and applicable compliance standards, including GDPR, HIPAA, and SOX.
Demonstrated ability to lead architecture reviews and provide technical direction without direct authority.
Strong analytical and problem-solving skills, including experience with performance tuning and optimization.
Effective written and verbal communication skills, with the ability to explain complex technical concepts, requirements, and results to technical and non-technical stakeholders.

Nice To Haves

Demonstrated success delivering secure, scalable, and reliable enterprise data solutions that meet business and operational needs.
Experience driving standardization and governance across diverse systems, teams, and global environments.
Ability to connect architecture decisions to long-term business objectives and evaluate tradeoffs across innovation, compliance, security, cost, and sustainability.
Strong collaboration and influencing skills, with experience building alignment across IT, BI, analytics, security, compliance, and business teams.
Ability to make sound, timely decisions in ambiguous or evolving technical environments.
Intellectual curiosity and a practical approach to evaluating and applying emerging technologies.
Change agility and the ability to adapt to evolving technologies, priorities, and business needs while maintaining delivery focus.

Responsibilities

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.
Develop and maintain enterprise data models, integration frameworks, storage solutions, and architectural patterns across cloud, on-premises, and hybrid environments.
Define and maintain data solution architecture and governance frameworks that align technical decisions with long-term business objectives and enterprise goals.
Provide technical leadership throughout the project lifecycle, including architecture reviews, solution validation, performance tuning, deployment strategy, and resolution of complex technical issues.
Establish and promote architecture principles, engineering standards, and best practices across development teams to improve scalability, reliability, interoperability, and consistency.
Implement data quality, lineage, metadata management, backup, accessibility, security, and governance practices across diverse systems and global data environments.
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.
Collaborate with business stakeholders, data scientists, analysts, BI teams, and IT partners to translate business needs into clear technical designs and accessible data solutions.
Clean, transform, and organize raw data into usable formats and create analytical tools or programs that support analysis, reporting, and informed decision-making.
Evaluate and optimize existing data systems to improve performance, reliability, speed, and maintainability while managing complexity across multi-cloud and hybrid platforms.
Evaluate emerging technologies, make informed recommendations under uncertainty, and apply innovative solutions that balance business value with security, compliance, and operational risk.
Build strong cross-functional relationships, communicate complex technical concepts clearly to technical and non-technical audiences, and maintain stakeholder alignment throughout delivery.
Adapt technical approaches and priorities as technologies and business needs evolve while sustaining data quality, platform stability, and delivery commitments.