Senior Data Engineer

Who We Are At Firstup, our mission is to improve the employee experience at every moment that matters, large and small. As the communication pipeline for the world's workforce, we now serve 40 of the Fortune 100 companies, reaching and connecting more than 17 million employees daily.

Our employees are experts in the employee experience, workforce communications and technology. Joining Firstup means joining a movement to make work better for every worker. As the world’s first intelligent communication platform, Firstup meaningfully engages employees at every moment from hire to retire, and delivers engagement insights to help companies support, promote and retain their talent.

Our movement has taken root and is evident in our world-class customer base. Now we need your help. Ready to make a difference in the world?

The Senior Data Engineer will design and build reliable data solutions that translate complex product and business logic into scalable, well-tested data models and pipelines. This role requires deep expertise in SQL, query acceleration, and applying GenAI to both engineering workflows and data/analytics interfaces. They will partner across engineering, analytics, and business teams, contribute to shared codebases, improve data quality and observability, and help evolve the data architecture.

Responsibilities

Design, build, and maintain scalable data pipelines, warehouse models, and analytics solutions, balancing data quality, business value, and speed. Build and maintain natural language interfaces to data and analytics, applying GenAI/LLM techniques to make data more accessible across the business.

Use GenAI coding tools and practices in daily development to improve code quality, testing, and delivery speed. Continuously evaluate new technologies that could improve and scale the team's data platform and technology stack. Establish and follow standards for SQL development, data modeling, testing, documentation, code reviews, and production support.

Support production data pipelines through on-call rotation and incident response, partnering with engineering, analytics, and business teams. Document and maintain expertise in the technology stack and product domain, translating business needs into technical solutions with product management. Minimum

Qualifications

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 working with and maintaining multi-tenant SaaS experiences Experience building natural language interfaces over data warehouses, including applying GenAI/LLM techniques to data and analytics Enterprise-level experience with at least one large-scale analytical data warehouse or query engine: StarRocks, Amazon Redshift, Snowflake, Databricks, or Trino Expertise writing, optimizing, and analyzing SQL 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 Proficiency in python.

Preferred Qualifications

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.