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1 день назад

Senior Data Engineer (SaaS)

138 942 - 181 397$
Формат работы
remote (только USA)/hybrid/onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Senior Data Engineer (SaaS): Build and maintain pipelines and analytical data models for AI Impact Reports, DX benchmarks, and industry-facing research with an accent on SQL, Postgres, data quality, and reproducible infrastructure. Focus on designing scalable ETL/ELT systems, handling large messy datasets, and documenting schemas and transformation logic for self-service analytics.

Location: Remote, hybrid, or office-based; DX is headquartered in Salt Lake City, United States. Hiring is available in any country where hirify.global has a legal entity.

Base salary: $138,942–$181,397 in Zone C, $150,660–$196,695 in Zone B, or $167,400–$218,550 in Zone A.

Company

hirify.global develops collaboration software, while DX provides SaaS products and research focused on developer experience, engineering productivity, and AI measurement.

What you will do

  • Build and maintain ETL/ELT pipelines that transform live product data into research-ready datasets in Postgres, data lakes, and analytics warehouses.
  • Design and optimize data models for AI Impact Reports, DX Core 4 benchmarks, and industry publications.
  • Collaborate with research and engineering teams to translate analytical requirements into scalable, reproducible data infrastructure.
  • Validate data quality, definitions, edge cases, and consistency across recurring analyses.
  • Provide ad hoc data pulls for research, Sales, Customer Success, and product teams.
  • Document schemas, transformation logic, data dictionaries, and pipeline dependencies.

Requirements

  • Strong SQL skills, including complex queries, query optimization, and analytical data modeling.
  • Hands-on experience with Postgres or similar relational databases and semi-structured JSONB or nested data.
  • Experience building and maintaining ETL/ELT pipelines from production systems to analytics-ready formats.
  • Experience cleaning, normalizing, and validating large, messy datasets at scale.
  • Strong documentation habits and the ability to manage recurring reporting deadlines with minimal oversight.

Nice to have

  • Experience with SaaS product data, telemetry, or event-driven data.
  • Familiarity with Git, GitHub, GitLab, Bitbucket, CI/CD metrics, or Jira data.
  • Exposure to survey data, time-series analysis, or benchmarking methodologies.

Culture & Benefits

  • High-ownership role covering the full pipeline from raw product data to research-ready datasets.
  • Research environment informed by the DORA, SPACE, and DevEx frameworks.
  • Health and wellbeing resources.
  • Paid volunteer days and additional local benefits.
  • Work options include office-based, remote, or hybrid arrangements.

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