Principal Data Engineer

Accountabilities:

• Own the end-to-end architecture of the data warehouse and reporting layer, defining modeling standards, data structures, and evolution patterns across Snowflake-based systems.

• Develop and maintain analytics engineering solutions, including SQL and dbt models that power core business reporting and downstream consumption.

• Partner cross-functionally with engineering, product, analytics, and business stakeholders to translate data needs into scalable technical solutions and close critical data gaps.

• Design and enhance platform integrations between upstream product systems and the warehouse, including schema automation and data flow optimization.

• Build and enforce data quality frameworks, including testing, validation, and monitoring processes to ensure reliable and trustworthy datasets.

• Implement observability practices and define data SLAs/SLOs while supporting light on-call responsibilities for production data systems.

• Own and extend Python-based data pipelines running on AWS services such as Glue, Lambda, and Step Functions, including API-based ingestion and outbound data delivery.

• Provide technical leadership and mentorship, driving engineering best practices, code quality, and architectural consistency across the data organization.

Requirements:

This role requires extensive experience in data engineering or analytics engineering at a senior or principal level, with strong architectural ownership of large-scale data platforms. Candidates should bring deep expertise in Snowflake, SQL, and relational data modeling, along with strong experience in dbt-based transformation workflows. Advanced Python skills are required, particularly for building and maintaining data pipelines on AWS (Glue, Lambda, Step Functions) and managing infrastructure via AWS CDK. Experience integrating with third-party APIs, including handling authentication, retries, and reliability constraints, is essential. Strong systems thinking, communication skills, and the ability to influence across technical and non-technical stakeholders are critical. Experience building reliable, observable data systems and mentoring engineers is also expected. A background of 10+ years in data-related roles is typically required.

Benefits:

• Competitive base salary range of $220,000 – $250,000 per year (based on experience and qualifications)

• Equity participation in an early-stage, high-growth environment

• Comprehensive health, dental, and vision insurance coverage

• Flexible paid time off policy supporting work-life balance

• 401(k) retirement plan with financial guidance support

• Collaborative, high-caliber team environment with strong technical peers

• Opportunity to shape core data architecture with significant business impact

• Additional wellness and employee support programs.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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