Senior Data Engineer (US)

Role overview A senior data engineering role focused on designing and shipping reliable, scalable data solutions that translate complex product and business logic into well-tested models and pipelines. The work combines deep SQL and distributed-systems expertise with applied GenAI, including natural-language interfaces that make analytics more accessible across the business.

Responsibilities - Design, build, and maintain scalable data pipelines, warehouse models, and analytics solutions, balancing data quality, business value, and delivery speed - Build and maintain natural-language interfaces over data and analytics using GenAI/LLM techniques - Apply GenAI coding tools and practices in daily development to improve code quality, testing, and delivery speed - Evaluate new technologies that could improve or scale the team's data platform and stack - Establish and uphold standards for SQL development, data modeling, testing, documentation, code reviews, and production support - Support production data pipelines via on-call rotation and incident response, partnering with engineering, analytics, and business teams - Document domain expertise and translate business needs into technical solutions alongside product management

Requirements - Bachelor's degree in Computer Science or related field, or equivalent professional experience - 8+ years building reliable, high-performance, large-scale distributed systems with an emphasis on streaming and data pipelines - Experience maintaining multi-tenant SaaS environments - Experience building natural-language interfaces over data warehouses and applying GenAI/LLM techniques to data and analytics - Enterprise-level experience with at least one large-scale analytical warehouse or query engine: StarRocks, Amazon Redshift, Snowflake, Databricks, or Trino - Strong SQL skills, including writing, optimizing, and analyzing queries - Hands-on experience building and operating distributed data platforms on AWS or GCP - Hands-on experience with streaming platforms such as Kafka and Spark - Experience scaling data modeling and warehousing, plus proficiency in Python

Nice to have - Experience with Cube or other semantic layers - Experience with scheduling tools such as Airflow - Familiarity with the BI tool Metabase - Proficiency in Ruby on Rails, React, or other adjacent languages

Benefits and work setup - Expected base salary range $155,000–$170,000, with starting pay influenced by location, experience, education, and skills - Remote work with a casual, friendly environment - Strong PTO program, health benefits, and leadership support for personal and professional growth