Sr. Analytics Engineer (Brazil and Argentina Only)

Niche · Argentina · posted today ago

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About this role

About Niche

Niche is the leader in school search. Our mission is to make researching and enrolling in schools easy, transparent, and free. With in-depth profiles on every school and college in America, 140 million reviews and ratings, and powerful search tools, we help millions of people find the right school for them. We also help thousands of schools recruit more best-fit students, by highlighting what makes them great and making it easier to visit and apply.

Niche is all about finding where you belong, and that mission inspires how we operate every day. We want Niche to be a place where people truly enjoy working and can thrive professionally.

About The Role

**We are currently recruiting for this role in Argentina and Brazil only. We will not be considering US based candidates at this time. All interviews are being held remotely. If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.**

**Only applications/resumes written in English will be accepted.**

We are looking for a Senior Analytics Engineer to join the Data Engineering team. You’ll architect, build, and scale our enterprise data models, translating complex raw data into clean, business-ready datasets while driving data accuracy, comprehensive documentation, observability, semantic consistency, and optimal warehouse performance. You will lead the design and maintenance of modular dbt models, semantic layers, and BI views for consumption by business analysts, data scientists, and executive stakeholders. This is an exciting opportunity to act as a technical leader on our team as we build the next generation of our analytics platform and semantic capabilities. You’ll be reporting to the Manager, Data Engineering (Core).

What You Will Do

Proactive Business Context & Integration: Partner directly with cross-functional executive stakeholders to translate evolving business strategy into robust analytics architecture, proactively embedding rich context, governance, and self-service capabilities across the data layer
Dimensional Modeling Leadership: Architect, document, and maintain complex Kimball dimensional models, standardized metric definitions, enterprise warehouse transformation logic, and scalable BI datasets tailored for high-stakes decision-making
Semantic Layer and AI Architecture: Design, build, and govern production-grade data models that power the enterprise semantic layer, enabling seamless AI/ML integrations and business-wide self-service analytics
Observability, Quality & Standards: Establish and enforce best-in-class data quality, automated testing, lineage tracking, cost optimization, and proactive alerting frameworks across all dbt transformation pipelines
.Process Optimization & Scaling: Evaluate and refactor legacy business logic and fragmented query architectures, standardizing disparate analyst workflows into modular, highly scalable semantic pipelines
Governance, Security & Mentorship: Drive enterprise data governance, metric standardization, and secure access controls, establishing single-source-of-truth definitions while mentoring junior and mid-level engineers in technical best practices

Within 1 Month:

Immerse yourself in the company culture, get to know your team, and establish relationships with key business and technical stakeholders
Deep dive into our data platform architecture, transformation pipelines, semantic models, and core business metric definitions
Participate actively in team ceremonies and begin reviewing current architecture, dbt models, and system performance
Deliver on initial high-impact analytics engineering user stories, demonstrating quick value within our existing pipeline frameworks

Within 3 Months:

Take ownership of key analytics engineering initiatives to expand our semantic layer, support complex reporting needs, and shape our technical roadmap
Drive root-cause analysis for complex data logic issues, performance bottlenecks, and modeling edge cases
Identify structural gaps in data transformation processes and propose scalable architectural enhancements to the team

Within 6 Months:

Lead critical workstreams in building our next-generation analytics platform, including advanced dbt models, semantic layer abstractions, and enterprise BI frameworks
Independently own key domain models and serve as a technical reference point for complex analytics engineering projects
Drive the evolution of business metric definitions and data governance standards across cross-functional domains

Within 12 Months:

Deliver foundational contributions to our overall analytics platform strategy, significantly advancing our semantic layer capability and company-wide decision-making infrastructure
Establish yourself as a recognized subject matter expert and technical leader within analytics engineering, elevating team standards and mentoring fellow engineers

What We Are Looking For

Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field (or equivalent practical experience)
6+ years of experience in analytics engineering, data engineering, or enterprise data modeling
Proven track record of architecting, deploying, and maintaining mission-critical, production-grade data transformation workflows and enterprise semantic models
Expertise in applying dimensional data modeling techniques (Star Schema, Kimball methodology) and leveraging dbt and advanced semantic layer tools to standardize complex metric logic across multi-functional organizations
Extensive experience modeling complex business domains (e.g., Salesforce, Google Analytics, ad platforms), product usage metrics, and unstructured/semi-structured data (JSON) for enterprise BI consumption
Strong software engineering background applied to data, including advanced git workflows, continuous integration/continuous deployment (CI/CD), modular architecture design, and comprehensive code documentation
Advanced proficiency in SQL, dbt (including macros, packages, and performance tuning), Snowflake, Python, Git, and modern BI platforms (e.g., Looker, Tableau)
Deep expertise with Google Analytics, marketing/ad/social media platforms, CRM/Salesforce systems, and designing custom semantic metrics at scale
Comprehensive understanding of modern data stack architecture, transformation strategies, semantic layer implementation, automated testing, governance, and BI integrations
Self-directed technical leader, strategic problem solver, highly attentive to detail, exceptional communicator, and driven by metric standardization, performance optimization, and rigorous technical documentation

Interview Process

Candidate experience is a top priority for our talent and hiring teams. We believe in providing a transparent, authentic and comprehensive interview process where you have the opportunity to learn about us while we get to know you and your experience. The interview process is outlined here: