Engineering Data Analyst, R&D Operations - CDMX
At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers. When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the microphone and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.
Engineering Data Analyst, R&D Operations - CDMX
Why We Have This Role
Our Product, Engineering, and UX teams need reliable data to make decisions. This includes metrics that measure what matters, dashboards that answer recurring questions, and datasets that power deeper analysis. As a Data Analyst on the PXE Analytics & Data Science Team, you'll build and maintain the data products, including the dashboards and metrics product and engineering leaders use to make decisions.You'll partner with Product Managers, Engineers, and Designers to define the right metrics, build Tableau dashboards and SQL-based datasets, and ensure the data they rely on is accurate and trustworthy. At more senior levels, you'll own strategic metrics, help answer complex business questions, and work with stakeholders to develop new measurement frameworks.How You’ll Find Success
- Focus on data products becoming indispensable. Stakeholders integrate your dashboards and metrics into their key decisions and come back asking for more. They trust your work because it's accurate, well-documented, and clearly communicated.
- High standards: Your datasets are trustworthy. Your dashboards are accurate. Your documentation makes it easy for others to understand and use your work. You care about being right and catching mistakes before they become problems.
- Technical growth: You're constantly learning new tools and techniques. You experiment with new approaches to make data more digestible. You're comfortable with messy datasets and don't get stuck when things are ambiguous. You love learning about how and why the data is being used to make decisions and business and product context.
How You’ll Grow
- Technical Depth: You'll develop expertise in SQL, data modeling, visualization, and dbt. You'll work with modern data tools and large-scale datasets.
- Business Acumen: You'll learn how great products are built by partnering closely with Product Operations, Product Management, Engineering, and UX. You'll understand what metrics actually matter and why.
- Problem-Solving: You'll tackle complex data challenges—from reconciling inconsistent data sources to designing metrics that accurately measure user behavior. You'll learn to think like a data engineer and an analyst.
- Career Path: Strong performers can grow into analytics engineering roles (building dbt models and data infrastructure) or senior analyst roles (owning strategic metrics and cross-functional initiatives). We promote based on impact and technical growth.
Things You’ll Do
- Build and maintain dashboards and datasets: Create Tableau dashboards that answer recurring business questions. Write SQL queries to build datasets that power analysis and reporting. Ensure data products are accurate, performant, and well-documented.
- Support key metrics and reporting: Help populate data for metrics reviews. Maintain critical company metrics like Customer Maturity. Build datasets that support Golden Paths measurement and product performance tracking
- Answer strategic questions: Conduct ad-hoc analysis to help stakeholders understand user behavior, product performance, or business trends. Partner with Data Scientists when deeper statistical analysis is needed.
- Define and develop new metrics: At more senior levels, work with Product and Engineering stakeholders to identify what should be measured, design the right metrics, and build the infrastructure to track them over time.
- Partner with upstream data providers: Work with Engineering and Data Engineering teams to understand data sources, identify data quality issues, and define requirements for new signals or datasets. Hold partners accountable when needed.
- Enable stakeholders: Lead sessions to help teams understand and use the products you build. Write clear documentation that makes metrics and datasets accessible to non-technical users.
- Maintain data quality: Build processes and checks to ensure data assets are trustworthy. Catch errors before they impact decisions. Be the person who cares about getting it right.
What We’re Looking For On Your Resume
- Education & Experience: Bachelor's or Master’s degree in analytical disciplines (Business Analytics, Economics, Finance, Computer Science, Engineering, Statistics) or relevant work experience. 0-3 years of experience as a data analyst, analytics engineer, or related role (internships count).
- Technical skills: Strong proficiency in SQL. Familiarity with Python for data analysis. Experience with data visualization tools like Tableau, PowerBI or Looker.
- Proactive problem-solving skills: Evidence of proactively identifying issues and digging in to understand root causes and fix them.
- Clear communicator: Experience explaining technical concepts to non-technical stakeholders. Evidence of strong written communication skills.
- High standards with humility: Evidence of being detail-oriented. Evidence of humility and knowing when to ask for help.
- Nice to have: Experience with dbt for data modeling. Understanding of data warehouses and query optimization. Experience with Git and reproducible workflows.
What You Should Know About This Team
The PXE Analytics & Data Science Team has 3 specialized pillars: Data Science, Analytics, and Analytics Engineering.
- Data Science focuses on deep research, experimentation, and predictive modeling.
- Analytics focuses on operational reporting and structured insights.
- Analytics Engineering focuses on building reliable datasets and data infrastructure.
You will work alongside a passionate group of experts in Seattle and Mexico City, all dedicated to bringing the power of data to Qualtrics itself.
Our Team’s Favorite Perks and Benefits
- Hybrid Work Model: We gather in the office three days a week to collaborate, and work where we want the rest of the week.
- Career Action Planning: Personalized career planning to help you achieve your goals inside and outside Qualtrics.
- Wellness: Comprehensive benefits including a wellness reimbursement and mental health benefits.