Principal Data Engineer

Key Responsibilities

- Serve as a technical authority on data architecture, data modeling, and pipeline design, ensuring scalability, reliability, and maintainability across the platform.
- Define and guide the long-term architectural vision for our data platform and services, collaborating closely with product and engineering leadership.
- Partner with North American engineering and product teams to ensure global consistency in technical direction, design standards, and implementation patterns.
- Provide technical mentorship and oversight, guiding engineers on complex design and implementation challenges.
- Lead architectural design reviews and contribute to defining standards and best practices for data engineering across teams.
- Design and implement large-scale, high-performance data pipelines, ensuring efficient data flow, transformation, and quality assurance.
- Contribute to our Dev Ops culture, ensuring our solutions are observable, secure, and resilient in production.
- Stay current with emerging technologies and trends, proactively identifying opportunities to evolve our data architecture and toolset.
- Partner with cross-functional teams (Product Management, Data Science, Analytics, and Infrastructure) to align on data strategy, governance, and technical priorities.

Requirements

Experience

- 10+ years of experience in data or software engineering, with a strong focus on distributed systems and data infrastructure.
- Proven experience architecting and scaling large data platforms in a cloud environment-AWS.
- 5+ years of experience designing and optimizing data models, ETL/ELT pipelines, and orchestration workflows.
- Hands-on experience building and maintaining complex data ecosystems involving technologies such as Airflow, Snowflake, MS SQL Server, and .NET.
- Prior experience providing technical leadership and architectural guidance across multiple teams or projects.
- Experience working in globally distributed teams, collaborating across time zones and regions (especially North America).

Technical Skills

- Deep expertise in data orchestration and batch processing technologies (e.g., Apache Airflow).
- Advanced proficiency in SQL, Snowflake, and MS SQL Server.
- Strong programming skills in Python and C#, with emphasis on performance optimization and maintainability.
- Hands-on experience with AWS services (e.g., S3, Lambda, Redshift, Glue, ECS, Cloud Formation).
- Familiarity with streaming data architectures, containerization (Docker), and CI/CD practices.

- Experience with observability and monitoring for data systems (e.g., New Relic, Cloud Watch).
- Proven ability to evaluate and introduce new technologies that align with long-term platform strategy.

Soft Skills

- Strategic thinker with the ability to balance short-term delivery and long-term architectural goals.
- Strong communicator who can translate complex technical concepts across technical and non-technical audiences.
- Collaborative mindset, comfortable influencing and aligning teams across geographies and functions.
- Excellent analytical and problem-solving skills with a high attention to detail.
- Self-driven and proactive, with the ability to operate independently and make sound technical decisions.

Mindset

- Passionate about technical excellence and continuous improvement.
- Comfortable driving strategic architectural discussions while remaining hands-on with implementation.
- Curious, innovative, and eager to experiment with new technologies.
- Committed to building a robust, scalable, and future-ready data platform.