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Salary
$145k – $192k per year
Location
Remote (United States)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
Jobgether is a Belgian recruitment platform built entirely around remote and flexible work, aggregating openings from thousands of employers that allow work from outside an office. Its matching engine ranks roles against a candidate's skills, seniority and stated preferences on location and flexibility, rather than leaving people to filter a keyword search, and it verifies how genuinely remote each posting is. The company also runs an AI screening layer that shortlists applicants for employers, and publishes research and guidance on distributed work practices alongside the job marketplace itself.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Analytics Engineer based in United States.

Join a remote-first Data team building the data foundations behind an AI-native financial planning and analysis platform. In this senior role, you’ll own transformation pipelines that turn complex financial and operational data into reliable, decision-ready models. You’ll work across diverse data sources while balancing data integrity, performance, scalability, and customer-specific requirements. The role offers meaningful technical ownership, with opportunities to define architecture, engineering standards, and best practices. You’ll partner closely with Customer Success, Engineering, and other stakeholders to solve challenging data problems. You’ll also help determine where AI can accelerate development, documentation, and operational workflows. This is an opportunity to make a direct impact in a fast-growing environment while raising the bar for analytics engineering.

Accountabilities

    • Own and evolve client-facing data transformation pipelines, improving how data is integrated, modeled, documented, and delivered as the customer base and number of integrations grow.
    • Design and maintain robust data integrity tests in partnership with Engineering and Customer Success to identify and resolve issues before they affect customers.
    • Collaborate with Customer Success to understand reporting and data requirements, troubleshoot issues, and develop reliable transformations across diverse source systems.
    • Refactor and optimize critical data models and pipelines to improve performance, scalability, reliability, and maintainability.
    • Establish technical patterns, conventions, and best practices that can be adopted across the Data team.
    • Explore and implement AI-enabled approaches that accelerate transformation development, improve quality, and strengthen documentation.
    • Contribute through high-quality code, thoughtful code reviews, clear technical communication, and improvements to team processes and developer experience.
    • Help strengthen the broader engineering organization by coaching teammates, contributing to hiring and onboarding, and promoting strong data practices.
    • Requirements

      • Demonstrated experience owning transformation pipelines for financial or operational data from source integration through production-ready analytical models; experience with financial data is an advantage.
      • Strong SQL skills and hands-on experience with dbt or a comparable transformation framework, alongside solid knowledge of version control, testing, and deployment practices.
      • Strong understanding of the full data lifecycle, from source systems and ingestion through transformation and consumption, with the ability to make sound technical and architectural decisions.
      • Experience working with data technologies such as BigQuery, Python, Git, and CI/CD; familiarity with tools such as Airbyte, Fivetran, Merge, or Datadog is beneficial.
      • Proven ability to take ownership, operate independently in ambiguous situations, establish standards, and drive technical decisions without requiring constant direction.
      • Strong commitment to code quality, data integrity, documentation, performance optimization, and scalable engineering practices.
      • Excellent communication skills, with the ability to work effectively with both technical and non-technical stakeholders across Engineering, Customer Success, and business teams.
      • Ability to mentor and elevate teammates, contribute to hiring and onboarding, and thrive in a fast-paced, evolving environment.
      • Willingness and ability to work remotely within the Americas, with working hours aligned to a distributed team.
      • Benefits

        • Competitive US compensation: $145.000 - $192.000 annually, plus equity.
        • Fully remote work for candidates based in United States and other eligible locations across the Americas.
        • Flexible working hours designed to support autonomy and distributed collaboration.
        • Unlimited PTO to encourage sustainable performance and time away from work.
        • Regular in-person company retreats to build relationships and strengthen collaboration.
        • Company-provided MacBook Pro or Lenovo laptop.
        • Health insurance for eligible US employees.
        • RRSP program for eligible US employees.
        • Opportunity to work with modern data and AI technologies in a rapidly growing environment.
        • Meaningful opportunities for technical ownership, mentorship, professional growth, and team impact.
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