Senior Data Engineer
Summary
Senior Data Engineer at Firstup designs and builds scalable data pipelines, warehouse models, and GenAI/LLM-powered natural-language interfaces to data. Day to day the role centers on expert SQL, Python, streaming platforms, and cloud data platforms on AWS/GCP, plus on-call support for production pipelines.
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
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Design, build, and maintain scalable data pipelines, warehouse models, and analytics solutions, balancing data quality, business value, and speed.
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Build and maintain natural language interfaces to data and analytics, applying GenAI/LLM techniques to make data more accessible across the business.
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Use GenAI coding tools and practices in daily development to improve code quality, testing, and delivery speed.
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Continuously evaluate new technologies that could improve and scale the team's data platform and technology stack.
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Establish and follow standards for SQL development, data modeling, testing, documentation, code reviews, and production support.
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Support production data pipelines through on-call rotation and incident response, partnering with engineering, analytics, and business teams.
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Document and maintain expertise in the technology stack and product domain, translating business needs into technical solutions with product management.
Minimum Qualifications
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Bachelor's degree in Computer Science or related field, or equivalent professional experience.
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8+ years building reliable, high-performance, large-scale distributed systems, with an emphasis on streaming and data pipelines.
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Experience working with and maintaining multi-tenant SaaS experiences.
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Experience building natural language interfaces over data warehouses, including applying GenAI/LLM techniques to data and analytics.
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Enterprise-level experience with at least one large-scale analytical data warehouse or query engine: StarRocks, Amazon Redshift, Snowflake, Databricks, or Trino.
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Expertise writing, optimizing, and analyzing SQL.
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Hands-on experience building and operating distributed data platforms on AWS or GCP.
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Hands-on experience with streaming platforms such as Kafka and Spark.
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Experience scaling data modeling and warehousing.
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Proficiency in python.
Preferred Qualifications
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Experience with Cube or other semantic layers.
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Experience with scheduling tools such as Airflow.
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Familiarity with the BI tool Metabase.
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Proficiency in Ruby on Rails, React, or other adjacent languages.
Skills
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