[Hiring] Senior Principal Database Engineer @Enlyte

Role Description

This is a remote position and can be located anywhere in the US. We are seeking a Principal Data Engineer to design, build, and optimize modern data platforms that power enterprise analytics, reporting, machine learning, and AI initiatives.

• The ideal candidate combines deep technical expertise across cloud platforms, data architecture, and automation with the ability to translate complex business requirements into scalable, high-impact solutions.
• This role will partner closely with business stakeholders, analytics teams, data scientists, architects, and engineering teams to deliver secure, governed, and reliable data products that drive measurable business value.
• The Principal Data Engineer will design and maintain scalable data platforms and pipelines, develop and optimize cloud-based data architectures, and automate infrastructure provisioning using Infrastructure-as-Code tools.
• They will collaborate with data scientists, analysts, architects, and business leaders to gather requirements, troubleshoot complex technical issues, implement data quality controls, and improve platform governance and security.
• The role also involves mentoring engineers, conducting code reviews, evaluating emerging technologies such as GenAI and machine learning, and continuously improving data platform performance, reliability, and cost efficiency across cloud environments including AWS, Snowflake, Azure, and Databricks.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical field
• Equivalent combination of education and relevant work experience may be considered
• Master's degree in Computer Science, Information Systems, Data Science, or related field preferred
• 10+ years of progressive experience in data engineering, analytics engineering, business intelligence, or related technical roles
• Proven track record designing and delivering enterprise-scale data platforms and analytics solutions
• Demonstrated ability to lead technical initiatives and influence architectural decisions
• Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders
• Experience operating in fast-paced, highly collaborative Agile environments
• Ability to independently drive projects from concept through implementation and support
• Strong problem-solving mindset with a focus on business outcomes, automation, and continuous improvement

Requirements

• Advanced proficiency in SQL and Python
• Experience building and maintaining scalable ETL/ELT pipelines
• Strong expertise in PySpark and distributed data processing
• Experience designing enterprise data models and lakehouse architectures
• Deep understanding of data warehousing, data lakes, and modern data platforms
• Experience implementing data quality, monitoring, and governance frameworks
• Hands-on experience with AWS services such as S3, IAM, Glue, and Lake Formation
• Experience working with Snowflake, Databricks, Azure, or GCP
• Experience designing secure, scalable cloud-native data architectures
• Understanding of cloud security, identity management, and access controls
• Experience with Terraform or similar Infrastructure-as-Code tools
• Strong Git-based development practices
• Experience implementing CI/CD pipelines and deployment automation
• Knowledge of platform monitoring, optimization, and operational support
• Experience partnering with business stakeholders to translate requirements into technical solutions
• Ability to advise teams on best practices, architecture, and platform capabilities
• Experience working within Agile, Scrum, Kanban, or SAFe delivery frameworks
• Strong documentation, communication, and stakeholder management skills

Desired Skills & Experience

• Experience administering and scaling enterprise Snowflake environments
• Multi-cloud experience across AWS, Azure, and GCP
• Experience supporting machine learning, MLOps, or AI-enabled analytics platforms
• Hands-on experience with GenAI, Large Language Models (LLMs), and AI-powered automation solutions
• Experience leading cloud migrations from on-premises environments to cloud lakehouse architectures
• Experience developing platform governance, security, and cost-management strategies
• Experience building automated cloud provisioning frameworks and self-service data platforms
• Familiarity with dbt and modern analytics engineering practices
• Experience with Tableau or other business intelligence tools
• Proven ability to optimize cloud spending and improve platform efficiency
• Experience mentoring engineers, conducting code reviews, and establishing engineering standards
• Exposure to large-scale, high-volume data environments supporting enterprise analytics and data science workloads

Preferred Certifications

• Databricks Certified Data Engineer Associate
• AWS Certified Cloud Practitioner or higher-level AWS certifications
• Snowflake certifications
• Azure Data Engineer Associate
• Terraform Associate or related cloud infrastructure certifications

Benefits

• Medical, Dental, Vision
• Health Savings Accounts / Flexible Spending Accounts
• Life and AD&D Insurance
• 401(k)
• Tuition Reimbursement
• An array of resources that encourage a lifetime of healthier living
• Compensation depends on the applicable US geographic market. The expected base pay for this position ranges from $131,000 - $180,000.00 annually, based on skills, experience, and education.