Job Summary:
The Principal Data Engineer will provide technical leadership across the complete data ecosystem, encompassing transactional databases, data modeling, data pipelines, analytics, and platform architecture. The role is more closely aligned with Data Platform Engineering than traditional pipeline-focused Data Engineering. The engineer will help shape data architecture, tooling, engineering standards, and platform practices while ensuring effective integration between transactional and analytical systems. The ideal candidate will bring deep database knowledge, strong analytical and platform engineering expertise, and the ability to influence technical direction as the data platform evolves.
Key Responsibilities:
• Contribute to the design and evolution of the organization's overall data platform architecture.
• Evaluate and influence tooling, data architecture, engineering standards, guardrails, and ways of working.
• Assess and improve existing architectural approaches, recommending changes where appropriate.
• Design and guide data movement from transactional and operational systems into analytical platforms such as Databricks.
• Develop and maintain data models across conceptual, logical, and physical modeling layers.
• Work with multiple source systems and define effective approaches for integrating and managing data across the ecosystem.
• Apply domain-driven data architecture and design principles to support scalable and maintainable data solutions.
• Collaborate closely with platform engineering, DevOps, architecture, and analytics teams.
• Ensure effective interaction between transactional databases and analytical data platforms.
• Provide technical recommendations to improve platform scalability, reliability, performance, and maintainability.
• Take ownership of technical challenges and drive improvements in processes, architecture, and engineering practices.
• Support the evolution of the data platform by evaluating emerging technologies and recommending appropriate solutions.
Required Qualifications:
• Deep knowledge of database technologies and architecture.
• Strong understanding of transactional and operational databases.
• Strong analytical data and platform engineering knowledge.
• Understanding of data movement and integration from transactional systems into analytical platforms.
• Strong foundation in conceptual, logical, and physical data modeling.
• Experience working with multiple source systems and integrating data across enterprise environments.
• Familiarity with domain-driven data architecture and design principles.
• Experience with AWS cloud services and infrastructure.
• Experience with modern data analytics platforms such as Databricks, Amazon Redshift, or Snowflake.
• Ability to collaborate effectively with platform engineering, DevOps, and architecture teams.
• Strong problem-solving and analytical skills, with the ability to make independent technical recommendations.
• Self-directed approach with the ability to take ownership and work effectively in evolving environments.
• Curiosity and willingness to learn new technologies and adapt to changing platform requirements.
• Ability to challenge existing approaches constructively and recommend improvements to technical standards and practices.
Preferred Qualifications:
• Hands-on experience with Databricks.
• Experience with modern analytical data platforms such as Amazon Redshift or Snowflake.
• Experience in the energy industry, particularly for senior or lead-level data engineering roles.
• Experience supporting data migration initiatives and large-scale data platform transformations.
