SENIOR ANALYTICS ENGINEER

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. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1