Principal Data Engineer (PySpark)

About Us

Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust. 

The Role

We are seeking a Principal Data Engineer with deep expertise in PySpark to join our data team. This is a hands-on senior technical role for someone passionate about building scalable data systems, mentoring engineers and shaping data strategy.  You’ll architect systems that power high performance batch and real time data processing, enable advanced analytics and accelerate our AI initiatives. If you're the type of person who can't let a problem go until it's solved this is the role for you.

Key Responsibilities:

• Design and evolve scalable, distributed data infrastructure across cloud platforms
• Build and maintain real time and batch data processing pipelines supporting analytics and AI/ML workloads
• Develop and manage integrations with third party e-commerce platforms to expand our data ecosystem
• Ensure data availability, reliability and quality through monitoring and automated auditing
• Partner with engineering, AI and product teams on data solutions for business critical needs
• Mentor and support data engineers, establishing best practices and code quality standards 

You:

• 10+ years of software development and data engineering experience with demonstrated ownership of production grade data infrastructure
• Passionate about building great systems and solving problems
• Bachelor's degree in Computer Science or a related field, or equivalent practical experience.
• Deep expertise scaling Spark in production (Databricks, EMR, etc)
• Strong understanding of distributed computing and modern data modeling for scalable systems
• Proficient in Python with experience implementing software engineering best practices
• Hands-on experience with both relational (MySQL / PostgreSQL) and NoSQL (MongoDB, DynamoDB, Cassandra) databases
• Strong communicator with experience influencing cross functional stakeholders

Nice to Have:

• Experience working in early-stage, high-growth environments
• Familiarity with MLOps pipelines and integrating ML models into data workflows.

The expected salary for this role is $235,000 - 285,000 depending on skills and experience.