Sr. Marketing Analyst (Brazil & Argentina ONLY)

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 an experienced, analytically rigorous, and collaborative Senior Marketing Analyst to own how Niche measures and improves the performance of its marketing engine, on both sides of the marketplace. This is a senior individual contributor role on the Analytics team, embedded day to day with the marketing and growth teams and reporting to the Manager of Operational Analytics.

The Senior Marketing Analyst is the analytical owner of two connected domains:

• B2B marketing and pipeline analytics: how marketing-sourced demand becomes qualified leads, opportunities, and closed business.
• B2C growth and registration analytics: how students and parents find Niche across acquisition channels, register, and convert into engaged users.

This is a deeply embedded role. You will sit in marketing, B2B, SEO, and lifecycle meetings and workflows, develop first-hand awareness of how data is actually being used, where the gaps are, and what's needed before it becomes a problem. You will be a strategic partner to marketing leadership rather than a reporting function: proactively surfacing insights, pairing them with recommendations and clear next steps, and staying with the work through the decision it informs.

What You Will Do

B2B Marketing & Pipeine Analytics

• Build the measurement foundation for how Niche markets to schools and districts: define which metrics matter, how they are calculated, and where the reporting lives, so the business can see what is actually working
• Bring rigor to questions such as which channels and campaigns produce pipeline that closes, what a marketing-sourced lead is actually worth, and where demand generation investment should go next
• Develop leading-indicator reporting that gives marketing and sales leadership early signal on pipeline health rather than a retrospective read
• Own the B2B attribution model in Marketo Measure, including touchpoint and channel definitions and the data flow between Marketo, Salesforce, and Snowflake. Partner with Marketing and Sales to keep campaign tracking and lead and opportunity attribution reliable over time
• Support new business forecasting and pipeline reviews with clear, documented methodology and honest confidence levels

B2C Growth & Registration Analytics 

• Own registration and acquisition measurement end to end: registration funnel performance, campaign and channel attribution, and the connection between how a user arrived and what they went on to do on the platform
• Measure paid acquisition efficiency: cost per registration, cost per qualified lead, and how spend translates into users who actually convert. Partner with Growth Marketing on media mix and budget decisions, and build the forecasts behind them
• Serve as the analytical partner to Growth Marketing and Lifecycle: size opportunities, design and read out growth tests, troubleshoot tracking, and maintain the reporting the team runs on day to day
• Build and maintain the marketing dashboards and self-serve views that let growth, lifecycle, and leadership answer their own recurring questions
• Own organic search analytics: measure performance by page type, path, and traffic source (profiles, rankings, entity search), and quantify the impact of product decisions and algorithm updates
• Build the monitoring and daily reporting that surfaces organic traffic shifts before they become surprises, and keep traffic definitions consistent across dashboards and the semantic layer
• Partner with Product and Data Engineering to define the event tracking and data models this measurement depends on

Analytical Rigor & Influence 

• Model analytical rigor on marketing data: reproducible SQL, documented methodology, validated results, and a clear line between correlation and causation
• Review and pressure-test analyses from across the analytics team and from business partners, and sharpen how findings are framed and communicated
• Act as the subject matter expert on acquisition-funnel data sources and methodology: when analyses from Business or Product Analytics start at the top of the funnel, make sure they start from the right source, the right definition, and a method that will hold
• Mentor analysts informally and share techniques across the analytics team
• Partner with Data Engineering as the voice of the business: write clear measurement requirements, contribute directly to dbt models and the company-wide self-serve semantic layer, and QA what gets shipped
• Champion AI-assisted analytics in your own work and help colleagues adopt it by building and maintaining the skills, workflows, and context that make these tools reliable on Niche's data
• Present findings and recommendations to senior leadership with clear insight and a clear "so what"

What We Are Looking For

• Bachelor's degree in Business Administration, Data Science, Statistics, Economics, Marketing, or a related field. A Master's degree is a plus
• 5+ years of experience in marketing analytics, growth analytics, data analytics, or a closely related data function.
• Demonstrated experience owning marketing measurement end to end, from tracking implementation through to reporting and recommendation.
• Hands-on experience with consumer acquisition data: web analytics and paid media platforms (GA4, Meta, Google Ads, or equivalent), including campaign and channel attribution and its limitations.
• Direct experience with B2B marketing and pipeline analytics: lead and MQL lifecycle, multi-touch attribution, campaign and channel contribution to pipeline, and conversion through to closed business.
• Experience working with marketing automation, CRM, and attribution data (e.g., Marketo, Marketo Measure, Salesforce) and diagnosing problems in how they connect.
• Proven ability to translate complex analytical findings into clear, actionable insight for non-technical stakeholders, and to say plainly when the data won't support the question.
• Experience in a fast-paced, cross-functional environment with shifting priorities, and resilience in the face of ambiguity and change.
• Senior proficiency in SQL; comfortable writing, reviewing, and troubleshooting complex queries independently.
• Strong proficiency in data visualization and dashboarding platforms such as Streamlit, Tableau, Looker, or similar.
• Working knowledge of a modern data stack: Snowflake, dbt, and version-controlled analytics work.
• Comfortable with experimentation and quantitative methods: designing and reading out A/B and growth tests, sizing effects honestly, and knowing when a result is signal and when it isn't.
• A genuine practitioner of AI-assisted analytics: comfortable using tools like Claude Code in your own work, and rigorous about validating what comes back.
• Comfort operating as a senior IC: influencing without authority, working self-directed on complex and ambiguous problems, and mentoring peers.

Nice to Have

• Experience with Python or R.
• Direct experience with SEO analytics: indexation, page-level organic performance, and technical SEO measurement.
• Experience contributing to a semantic layer or self-serve metrics layer.
• Background in SaaS, education technology, or marketplace analytics environments.
• Experience in the education sector or working with schools and colleges.

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:

• Video Interview with Talent Acquisition Partner - 30 Minutes

• Video Interview with Hiring Manager - 45 Minutes

• Team Interview - 3 separate 30 Minute Interviews

• Case Study & Presentation

• Hiring Manager follow-up - 30 Minutes 

**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.**