Principal Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and directly contribute to essential platform components, such as ingestion pipelines, transformation frameworks, data models, and orchestration.

• Establish and refine the multi-quarter technical roadmap for the data platform, balancing new features, reliability enhancements, and reductions in technical debt in line with the overall platform architecture.

• Lead the assessment and adoption of tools across the entire stack, ensuring that selections are well-founded and aligned with the future direction of the platform.

• Facilitate architecture reviews and design discussions, ensuring that decisions are well-justified, documented, and comprehensible to the team.

• Navigate ambiguity by posing the right questions early regarding data quality, schema evolution, and downstream dependencies, while identifying risks before they escalate into crises.

• Convey intricate data infrastructure decisions to non-technical stakeholders without oversimplifying, and translate vague product requirements into detailed engineering tasks and acceptance criteria.

• Collaborate closely with data science leads and cross-functional teams to identify dependencies and constraints early, prioritizing enhancements that boost productivity.

• Maintain an efficient yet effective backlog and planning process, keeping the team focused and unimpeded.

• Mentor and develop engineers with an emphasis on enhancing technical depth — delegate impactful tasks, collaborate on challenging issues, and create opportunities for others to grow.

• Establish standards for code reviews, testing philosophies, and engineering best practices that elevate the entire team, including data validation, pipeline testing, and schema management.

• Ensure the reliability of data systems in production — ensuring they are instrumented, observable, operable, and have defined SLAs for freshness, completeness, and accuracy.

⛳️ Requirements

• Minimum of 8 years of experience in data engineering, including at least 2 years in a principal or staff capacity.

• Demonstrated ability to design and assess end-to-end data platforms encompassing ingestion, transformation, storage, and serving, with well-defined contracts between layers.

• In-depth knowledge of data pipeline design, with proficiency in the patterns and trade-offs associated with batch and streaming pipelines at scale.

• Strong grasp of data modeling and storage strategies.

• Solid software engineering fundamentals, with the expertise to assess code quality and establish architectural standards.

• Extensive experience with cloud data infrastructure (AWS, GCP, or Azure) and its associated ecosystem.

• Proven ability to lead technical teams, set strategic direction, and develop engineers without relying solely on formal authority.

🏝️ Benefits

• Competitive salary and benefits package, including health, dental, vision, and employer-matched 401k.

• Flexible work environment with adaptable paid time off.

• Opportunities for mentorship and growth within a collaborative team.