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Associate Engineer, Investment Data & Analytics (FinTech)

155 000 - 165 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
junior/middle
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Associate Engineer, Investment Data & Analytics (FinTech): Building, testing, and operating data pipelines and datasets for private-markets investment and research teams with an accent on financial data engineering, platform reliability, and data quality. Focus on designing ETL transformations, monitoring production workflows, reconciling datasets, and automating manual investment-data processes.

Location: Boston, with a hybrid work arrangement and 18 remote workdays per quarter subject to manager approval.

Base salary: $155,000–$165,000 per year, plus eligibility for a discretionary annual bonus and other total rewards.

Company

hirify.global is a global investment firm developing technology to systematize private-markets analysis and scale fund management.

What you will do

  • Build, test, and deploy pipelines and transformations across financial and economic datasets.
  • Run and monitor production data workflows, troubleshoot failures, and implement alerting, logging, automated testing, and CI/CD practices.
  • Develop data validation and reconciliation checks, track pipeline-health KPIs, and perform root-cause analysis for data issues.
  • Collaborate with data engineering, DevOps, application, investment, product, and operations teams to clarify requirements and deliver documented solutions.
  • Perform deep data analysis for investment-model research and identify manual processes suitable for automation.

Requirements

  • Demonstrated ability in data engineering and analysis, including data-centric testing and deployment of FinTech applications.
  • Proficiency in SQL, including MSSQL or an equivalent relational database, and Python.
  • Experience building ETL pipelines for large datasets.
  • Experience with DBT and Azure Data Factory and Pipelines.
  • Strong analytical, organizational, and problem-solving skills with outstanding attention to detail.
  • Genuine interest in financial markets and comfort working in a Scrum/agile SDLC environment.
  • 3–5 years of data engineering or data operations experience preferred.
  • Bachelor of Science, Master of Science, or equivalent degree in Computer Science.

Nice to have

  • Exposure to Snowflake, MS Synapse, or Power BI.
  • Exposure to private-equity or investment-management data.
  • Experience partnering with product, application, and operations teams.

Culture & Benefits

  • Collaborative, open-door environment focused on diversity, inclusion, mutual respect, and innovative thinking.
  • Hybrid work with 18 remote days available per quarter subject to manager approval.
  • Comprehensive total rewards package may include retirement contributions, health insurance, income protection, paid time off and leave benefits, and well-being programs.
  • Annual bonus eligibility is discretionary and based on individual and firm performance.

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