Senior Data & Analytics Engineer

The Opportunity

The Senior Data & Analytics Engineer will own the reliability and evolution of the company’s data and analytics infrastructure, including data models, the warehouse, pipelines, integrations, and billing data. This role moves beyond reporting into data modeling, analytics architecture, instrumentation strategy, and cross-functional enablement. The person will independently identify opportunities, translate ambiguous business needs into clear analytics initiatives, and drive those initiatives from definition through implementation and adoption.

This individual will serve as the technical bridge between raw data and business decision-making, leading the design of robust data models, optimizing SaaS metrics, and ensuring accurate tracking across web and native applications. Success in this role requires ownership of both technical quality and business outcomes.

This is a senior individual-contributor role. The person is expected to demonstrate leadership through initiative ownership, sound judgment, proactive communication, and cross-functional influence. People management is not currently a requirement.

Responsibilities

Analytics Architecture & Data Modeling

• Design, build, and maintain scalable analytics data models to support business reporting and decision-making.
• Build, maintain, and troubleshoot ETL/ELT pipelines and data transformations.
• Own source-of-truth definitions and reconcile data across application, billing, and analytics systems.
• Own the structure and optimization of SaaS metrics, including subscription lifecycle, billing, churn, retention, LTV, and revenue analytics (Stripe).
• Ensure data integrity, consistency, and governance across systems.
• Monitor data flows and proactively detect, troubleshoot, and recover from pipeline failures or missing data.
• Partner with Engineering to assess the data impact of product releases and prevent breaking changes to collection systems.

Instrumentation & Event Tracking

• Define tracking specifications and lead the auditing and validation of event strategy across web and native applications in partnership with Engineering.
• Partner with engineering and product teams to define, implement, and audit tracking standards.
• Improve reliability and completeness of user event data (Segment, Mixpanel, or similar tools).
  
  
  

Data Analysis & Insights

• Perform advanced analysis using SQL and Python to generate actionable insights.
• Identify trends, risks, and growth opportunities within SaaS performance metrics.
• Translate complex datasets into clear business recommendations for leadership.
  
  
  

Analytics Platform Ownership

• Build and continuously improve the company’s analytics framework and reporting ecosystem.
• Develop dashboards and data visualization assets that provide reliable, self-serve insights for stakeholders.
• Optimize data pipelines and queries for performance and scalability.
  
  
  

Cross-Functional Collaboration

• Lead cross-functional analytics initiatives by aligning Product, Engineering, Customer Success, and Finance on the business problem, requirements, KPIs, measurement approach, milestones, and expected outcomes.
• Act as the subject-matter expert in analytics and data interpretation across the organization.
• Proactively surface relevant trends, risks, and opportunities, and provide leadership with clear recommendations and forecasting support.
  
  
  

Initiative Leadership & Ownership

• Independently identify and prioritize analytics opportunities aligned with business needs.
• Lead analytics initiatives from problem definition and stakeholder alignment through implementation, adoption, and measurement of results.
• Establish clear scope, milestones, success criteria, and ownership for assigned initiatives.
• Proactively communicate progress, risks, tradeoffs, and decisions needed to the manager and relevant stakeholders.
  
  
  

Qualifications

• 5+ years of experience in analytics engineering, analytics, or related data-focused roles, preferably in a SaaS environment, including demonstrated ownership of complex cross-functional initiatives.
• Strong proficiency in SQL (advanced querying, modeling, performance optimization).
• Experience using Python for data analysis and automation.
• Experience designing, building, and maintaining databases, data warehouses, ETL/ELT pipelines, and integrations across multiple business systems.
• Experience with cloud data infrastructure; AWS experience is preferred.
• Strong understanding of SaaS metrics (MRR, churn, CAC, LTV, retention cohorts, subscription analytics).

Nice to Have

• Experience with Amplitude or comparable product analytics tools.
• Experience working with SaaS subscription and billing data, including Stripe.
• Experience with data visualization platforms such as Looker, Tableau, or Power BI.
• Experience partnering with Engineering on instrumentation and data-impacting product releases.

Desired Characteristics

• Strong attention to detail and commitment to data accuracy.
• Self-sufficiency and sound judgment.
• Fast learning and adaptability.
• Proactivity and a willingness to identify and solve problems without waiting for detailed direction.
• Demonstrated ability to communicate proactively, manage stakeholder expectations, surface risks and tradeoffs, and translate technical findings into business impact.
• Demonstrated ability to operate effectively with ambiguity, establish direction, and move initiatives forward without requiring detailed day-to-day guidance.

Compensation: USD $5,200–$6,000 per month, based on relevant experience and qualifications.

Benefits:

• 15 days of paid time off in your first year, increasing to 20 days in your second year, covering vacation, personal time, and sick leave.
• Paid company-observed U.S. holidays.
• Reimbursement of up to USD $125 per month toward your own medical coverage.

Location: Remote — Latin America. Candidates must be available to work with substantial overlap during standard U.S. Mountain Time business hours.