Senior Data Engineer

Role Overview

The Senior AI/ML Data Engineer is a hands-on technical contributor responsible for designing, building, and maintaining the data infrastructure that powers AI/ML product features across the organization.

What You Will Do

Design, build, and maintain ETL pipelines, partner with cross-functional teams, investigate and resolve data integrity issues, ensure data security and compliance, automate data ingestion and processing, and develop and maintain complex datasets.

Why It Might Be a Fit

The ideal candidate is someone who thrives in a fast-moving product engineering environment, can navigate ambiguity in requirements, take ownership of problems, and maintain a high standard of documentation and data quality.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 4-6 years of experience in data engineering or related fields, with a focus on AI/ML
• Strong Python skills, including experience with migration frameworks (e.g., Alembic, SQLAlchemy), and production-grade data processing scripts
• Advanced SQL across both transactional databases (PostgreSQL or similar) and columnar data warehouses (AWS Redshift strongly preferred)
• Proficiency in cloud services (e.g., dbt, AWS, Azure, GCP)
• Proficiency with AWS services: Redshift, S3, Lambda, IAM
• Strong Git and GitHub skills, including branching strategies, pull request workflows, and code review practices
• Expertise in building scalable, fault-tolerant data pipelines
• Excellent problem-solving and analytical skills, with the ability to identify and address performance bottlenecks
• Leadership Skills: Experience mentoring junior engineers or leading small teams, with strong technical leadership capabilities
• Collaboration Skills: Excellent communication and teamwork skills, with the ability to work effectively in cross-functional teams

Benefits

• Competitive salary
• Equity
• Healthcare
• PTO
• Retirement
• Learning budget
• Parental leave
• Wellness
• Remote flexibility