Job Description

We are hiring Senior Analytics Engineer Data Architecture

ON SITE | Medellín, Colombia

About the Role

Simpro is hiring a Senior Analytics Engineer to join our Data Team as a senior individual contributor.

This role is hands-on and highly business-facing, focused on building the trusted data architecture, models, documentation, and business logic that enable the company to make better decisions.

This is not a people management role, and it is not a front-end dashboard or visualization role.

The Data Team is responsible for creating the certified data foundation that downstream teams use for reporting, analysis, and self-service.

This role will be accountable for designing and maintaining that foundation, ensuring the data is accurate, well-structured, clearly documented, and connected to how the business actually operates.

A critical part of this role is connecting the dots.

You will work across Sales, Marketing, Finance, Revenue Operations, Product, and other business teams to understand how processes, systems, data, and KPIs fit together.

You will translate that understanding into scalable data models, clear definitions, and documentation that helps the business consume data consistently and safely.

Key Responsibilities

- Build and Own Core Data Models

Design, build, and maintain scalable data models in BigQuery using dbt.

Create certified datasets, tables, and views that downstream teams can use confidently for reporting, analytics, and decision-making.

- Serve as a Senior Individual Contributor

Operate as a hands-on technical contributor responsible for solving complex data modeling, business logic, and data architecture challenges.

This role does not manage a team.

Success depends on strong ownership, technical judgment, collaboration, and the ability to independently drive work from business question to documented data solution.

- Connect the Dots Across the Business

Work across Sales, Marketing, Finance, Revenue Operations, Product, and other teams to understand how business processes, systems, data flows, and KPIs connect. Identify where definitions, processes, or source-system logic are misaligned, and help create a clear, consistent data structure that reflects how the business operates.

- Leverage AI Securely to Optimize and Move Faster

Use approved AI tools, automation, and modern data practices to improve productivity, accelerate documentation, surface patterns, validate logic, and reduce manual effort.

Apply AI in a secure and controlled manner, ensuring sensitive data is protected and that outputs are reviewed, validated, and aligned to company governance standards.

- Define and Standardize Business KPIs

Partner with business stakeholders to define, document, and standardize key business metrics across the data layer.

This includes SaaS and subscription metrics such as ARR, MRR, churn, net revenue retention, gross revenue retention, expansion revenue, bookings, pipeline, conversion rates, and customer lifecycle metrics.

- Model the Sales and Revenue Funnel

Build data models that support the full go-to-market motion, including lead generation, marketing attribution, campaign performance, opportunity progression, pipeline creation, bookings, renewals, expansion, and retention.





Ensure the data architecture connects marketing activity, sales motion, customer activity, revenue outcomes, and business KPIs in a clear and consistent way.

- Own Documentation and Data Definitions

Create and maintain high-quality documentation for datasets, fields, transformations, business rules, metric definitions, lineage, assumptions, and known limitations.

Documentation is a core responsibility of this role.

Downstream users should be able to understand what the data means, where it comes from, how it is calculated, when it should be used, and where caution is required.

- Translate Business Logic into Data Architecture

Take complex business requirements and translate them into clean SQL logic, scalable schemas, reusable dbt models, and clear documentation.

Help stakeholders understand tradeoffs, dependencies, and implications when business rules, systems, or reporting requirements change.

- Strengthen Data Governance and Quality

Support data governance by enforcing modeling standards, naming conventions, testing, validation, documentation, and certification of production-ready datasets.

Proactively identify data quality issues, inconsistent logic, gaps in source systems, and downstream reporting risks.

Partner with the appropriate teams to resolve issues at the source where possible.

- Partner on Data Platform Best Practices

Collaborate with the Senior Data Architect and broader Data Team on architecture decisions, modeling standards, dbt best practices, platform optimization, and long-term data strategy.

Requirements

· 5+ years of experience in analytics engineering, data analytics, data modeling, business intelligence engineering, or data architecture-focused roles.

· Strong hands-on experience with Google BigQuery, including query optimization, partitioning, clustering, performance tuning, and cost management.

· Advanced SQL skills, with the ability to write clean, efficient, scalable, and well-documented queries.

· Hands-on experience with dbt, including data modeling, testing, documentation, lineage, and deployment practices.

· Experience working with ELT pipelines and data ingestion tools such as Fivetran.

· Experience working in a SaaS, software, subscription, or recurring revenue business model.

· Strong understanding of SaaS business metrics, including ARR, MRR, churn, retention, expansion, bookings, pipeline, and revenue growth.

· Strong understanding of the B2B sales motion, including lead-to-opportunity conversion, pipeline stages, opportunity management, bookings, renewals, and customer expansion.

· Ability to connect business processes, source-system data, and reporting requirements into a coherent data model.

· Strong documentation discipline, with the ability to explain complex data structures, business rules, dependencies, and metric definitions clearly.





· AI-first mindset with the ability to securely leverage approved AI tools and automation to improve speed, documentation quality, analytical rigor, and team productivity while maintaining strong data privacy and governance standards.

· Ability to operate independently as a senior individual contributor with strong ownership, follow-through, and judgment.

· Comfortable working across time zones in a distributed integral team environment.

Languages

• Fluent English, both written and spoken.

• Ability to lead meetings, provide professional guidance, and manage business communications in both languages.

Benefits

- Competitive salary in Colombian pesos (COP)

- Continuous training and mentoring.

- Work with a Leading Global company.

- Growth Opportunities: Join a growing team with plenty of room for career advancement.

- Collaborative Culture: Work alongside passionate professionals in an innovative environment.

- In-Office Role: Excellent opportunity to collaborate with Leadership in Medellin’s modern office.

If you meet the requirements, we’d love to start a conversation with you.

Simply fill out the application form, and we’ll be in touch to schedule your interview promptly.

Don’t miss your chance to work with a leading global IT company that’s on the rise!

**Only resumes in English will be considered for this position**

Requirements
· 5+ years of experience in analytics engineering, data analytics, data modeling, business intelligence engineering, or data architecture-focused roles.

· Strong hands-on experience with Google BigQuery, including query optimization, partitioning, clustering, performance tuning, and cost management.

· Advanced SQL skills, with the ability to write clean, efficient, scalable, and well-documented queries.

· Hands-on experience with dbt, including data modeling, testing, documentation, lineage, and deployment practices.

· Experience working with ELT pipelines and data ingestion tools such as Fivetran.

· Experience working in a SaaS, software, subscription, or recurring revenue business model.

· Strong understanding of SaaS business metrics, including ARR, MRR, churn, retention, expansion, bookings, pipeline, and revenue growth.

· Strong understanding of the B2B sales motion, including lead-to-opportunity conversion, pipeline stages, opportunity management, bookings, renewals, and customer expansion.

· Ability to connect business processes, source-system data, and reporting requirements into a coherent data model.

· Strong documentation discipline, with the ability to explain complex data structures, business rules, dependencies, and metric definitions clearly.

· AI-first mindset with the ability to securely leverage approved AI tools and automation to improve speed, documentation quality, analytical rigor, and team productivity while maintaining strong data privacy and governance standards.

· Ability to operate independently as a senior individual contributor with strong ownership, follow-through, and judgment.

· Comfortable working across time zones in a distributed global team environment.

Languages • Fluent English, both written and spoken.

• Ability to lead meetings, provide professional guidance, and manage business communications in both languages.

Required Skill Profession

Computer Occupations

📌 Senior Analytics Engineer, Data Architecture & Governance (Medellín)
🏢 Roca Alliances
📍 Medellín