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Senior Data Engineer

Firstup
Remote, USA
Full-time
Senior · 8+ years experience
Remote
USD 100000-140000 yearly / year
Discovered Yesterday
SQLStarRocksAmazon RedshiftSnowflakeDatabricksTrino
Free

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Key skills for this role

SQLStarRocksAmazon Redshift
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Full Job Posting

  • 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.
  • 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.
  • 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.

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