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6 дней назад

Senior Manager, Data Engineering

153 750 - 230 625$
Формат работы
hybrid
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 Manager, Data Engineering (Snowflake/Databricks): Building data engineering platforms, warehouses, and trusted analytical models for business intelligence and data science with an accent on architecture, data quality, and people leadership. Focus on designing facts, dimensions, snapshots, and SCDs, resolving production incidents, and developing a high-performing data engineering team.

Location: Atlanta, Georgia, United States. Office-first culture with three days per week in the office for most roles.

Annual base pay range: $153,750–$230,625 USD for candidates based in California, Colorado, Connecticut, Nevada, New York, Rhode Island, and Washington.

Company

hirify.global develops an AI-ready governance platform that unifies regulatory intelligence, automation, and data governance workflows.

What you will do

  • Lead and coach a team of data engineers while contributing hands-on to platform and data engineering architecture.
  • Design data architectures, models, facts, dimensions, snapshots, and slowly changing dimensions for business intelligence and data science.
  • Build and maintain trusted data models in Snowflake and Databricks using dbt, Airflow, and ELT tools.
  • Partner with data architects, business analysts, security teams, vendors, and cross-functional stakeholders on data strategy and controls.
  • Drive technical discussions, resolve production incidents, and establish standards for data quality, validation, and analytics.
  • Hire, retain, and develop data engineering talent through coaching and career development.

Requirements

  • Bachelor’s or master’s degree in computer science, engineering, or a related field.
  • 10+ years of professional data engineering experience, including critical outage incident command.
  • Extensive experience with data architecture, data warehousing, data modeling, ETL pipelines, and tool evaluation.
  • Strong data warehouse knowledge and ability to write complex SQL for raw-data processing, validation, and QA.
  • Experience with Python and extracting and transforming varied data formats.
  • Experience leading or working with distributed teams in a high-growth, fast-paced environment.

Nice to have

  • Experience applying AI in data engineering.
  • Experience designing warehouses for ACV, ARR, event history, identity resolution, deferred revenue, revenue metrics, experimentation, and audiences.
  • Experience managing distributed teams across geographies.

Culture & Benefits

  • Office-first working model with meaningful opportunities for in-person collaboration.
  • Comprehensive healthcare coverage and flexible paid time off.
  • Equity RSUs, annual performance bonus opportunities, and retirement account support.
  • 14+ weeks of paid parental leave.
  • Career development opportunities and company-paid privacy certification exam fees.

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