1 день назад
Senior Data Engineer (SaaS)
138 942 - 181 397$
Мэтч & Сопровод
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Описание вакансии
Текст:
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 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
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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