22 часа назад
Data Engineer
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer (dbt/Snowflake): Building analytics-ready data models, automated data pipelines, dashboards, and AI-enabled analytics tools for a business travel and expense platform with an accent on product and operational analytics. Focus on harmonizing acquisition data, analyzing high-volume datasets, defining metrics, and improving data quality and self-service reporting.
Location: Dallas, TX, United States; hybrid with on-site work required 3–4 days per week
Company
is an AI-powered business travel and expense platform for frequent travelers and finance teams.
What you will do
- Design, build, and maintain analytics data models, tables, and views using dbt and Snowflake.
- Develop and automate analytics-layer data pipelines with testing, monitoring, and data-quality controls.
- Partner with Product, Engineering, Operations, and business stakeholders to translate requirements into data solutions and define key metrics.
- Analyze large, complex datasets to identify insights for product and operational improvements.
- Build and maintain ThoughtSpot dashboards and reports for KPIs, product usage, and operational performance.
- Harmonize data definitions across business units and acquisitions, and develop AI-enabled tools for analytics automation and self-service access.
Requirements
- 2–3+ years of experience in data engineering, analytics engineering, or advanced data analytics.
- Advanced SQL skills and experience with data modeling, dbt, and cloud data warehouses; Snowflake is preferred.
- Experience building analytics pipelines, tables, and views while ensuring data quality.
- Hands-on experience with BI and data visualization tools, including dashboard and report development.
- Experience analyzing complex, high-volume datasets and communicating actionable insights.
- Python experience for data analysis or interaction with platforms and AI tools, plus the ability to work on-site 3–4 days per week.
Nice to have
- Experience with experimentation frameworks or statistical analysis, including regression and significance testing.
- Experience in product-centric or fast-paced environments and stakeholder management.
- Familiarity with versioning, testing, monitoring, and other engineering best practices.
Culture & Benefits
- High-performance environment focused on autonomy, collaboration, and excellence.
- Healthcare, insurance, wellness resources, and mental health support.
- Retirement savings programs and equity participation opportunities.
- Flexible time off, country-specific holidays, and paid parental leave.
- Connectivity and commuting support, company-provided lunches, and travel-related perks.
Hiring process
- Resumes may be evaluated with ’s AI-assisted employment decision tool, with final decisions made by human recruiters and hiring managers.
- Candidates may request a human-only application review.
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