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1 день назад

Manager, Analytics Engineering

165 000 - 195 000$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
lead
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
Manager, Analytics Engineering (Snowflake/dbt/AWS): Leading a remote analytics engineering team that operates the warehouse, ingestion, modeling, and data platform supporting risk, fraud, product, actuarial, and financial reporting with an accent on platform standards, reliability, and shared business models. Focus on managing engineers, evolving dbt and Snowflake architecture, hardening data quality, and automating operational workflows with AI assistance.

Location: Remote

Salary: $165,000–$195,000 per year

Company

hirify.global provides AI-driven post-purchase solutions for retailers, including automated customer service, returns and exchanges, fulfillment, product and shipping protection, and fraud detection.

What you will do

  • Lead, hire, onboard, and develop a remote team of analytics and data engineers.
  • Own the Snowflake warehouse, dbt repository, ingestion workflows, external tables, and AWS Glue/CDK data jobs.
  • Set standards for architecture, testing, documentation, CI, pull-request review, and change control.
  • Develop shared models for orders, contracts, claims, and service orders used by actuarial, risk, fraud, product, finance, and revenue teams.
  • Lead platform migrations, including moving dbt execution to Snowflake-native tooling and retiring legacy components.
  • Run on-call operations, monitoring, alerting, incident response, data-quality audits, self-service documentation, and AI-assisted operational workflows.

Requirements

  • At least 2 years of experience managing engineers on a data or analytics engineering team.
  • Advanced SQL and dimensional modeling experience.
  • Deep experience owning dbt repositories with version control, testing, pull-request review, CI, and change control.
  • Experience with Python and AWS data infrastructure, including Glue, Step Functions, Lambda, and CDK.
  • Experience operating reliable data platforms, including on-call, alerting, incident response, and root-cause analysis.
  • Strong written communication, prioritization, stakeholder partnership, and business-to-data-model translation skills.

Nice to have

  • Experience with actuarial, risk, fraud, warranty, insurance, service-contract, financial, or revenue analytics.
  • Experience with privacy and deletion compliance, BI administration, or AI-assisted engineering workflows.

Culture & Benefits

  • Collaborative environment with colleagues from diverse backgrounds.
  • Medical, dental, and vision benefits.
  • Stock in an early-stage startup.
  • Generous, flexible paid time off.
  • 401(k) with financial guidance from Morgan Stanley.

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