Analytics Engineer - CDI
We are looking for an Analytics Engineer to own and scale Tarmac’s customer analytics platform.
Powered by Omni Analytics and embedded within our products, the platform helps operational teams at airports, airlines, and ground-handling companies worldwide understand their performance, identify improvement opportunities, and make better operational decisions. It is also used by Tarmac’s internal teams to support customers and guide product development.
You will be responsible not only for the underlying data models, but also for the overall customer analytics experience: understanding users’ operational and business needs, defining the right metrics, and enabling them to access data, explore performance, build dashboards, and use AI to generate actionable insights.
Own the development and continuous improvement of Tarmac’s analytics platform, including its architecture, semantic layer, embedded experience, permissions, reliability, and roadmap.
Develop a strong understanding of our customers’ operations, challenges, and business objectives, and translate them into scalable analytics capabilities.
Build and maintain reliable, scalable data models in dbt that power both customer-facing analytics and internal reporting.
Configure and structure Omni Analytics to provide an intuitive, consistent, and AI-powered experience for users with different levels of data expertise.
Work closely with customers and with Product, Engineering, Design, Operations, and Customer Success to turn recurring needs into reusable product capabilities rather than one-off solutions.
Define meaningful metrics and ensure that business definitions remain consistent across products and customers.
Enable customer and internal self-service through well-designed topics, reusable dashboards, clear documentation, training, and light-touch support.
Monitor platform usage, performance, and adoption, combining behavioral data and direct customer feedback to continuously improve the analytics experience and its business impact.
Maintain high standards of data quality, security, and governance through automated testing, monitoring, lineage, documentation, and appropriate data-access controls.
Optimize our Redshift and DBT environment, including incremental models, query performance, reliability, and deployment workflows.
Use AI tools and MCP integrations to accelerate development, documentation, investigation, and analytical workflows.
Requirements
- 3-5 years of experience in Analytics Engineering, Data Engineering, Business Intelligence, or a similar data-focused role.
- Advanced SQL skills and strong hands-on experience with DBT and a cloud data warehouse such as Redshift, Snowflake, or BigQuery.
- Experience working with a modern BI or analytics platform such as Omni, Looker, Tableau, or Power BI.
- Strong understanding of dimensional modeling, semantic layers, metric definitions, incremental pipelines, and data governance.
- A customer and product mindset, with a genuine interest in understanding operational challenges and turning analytics into a useful, user-facing product, not simply a collection of dashboards.
- Experience implementing data quality tests, monitoring, documentation, and reliable Git-based CI/CD workflows.
- Excellent communication skills, with the ability to collaborate with both technical and non-technical stakeholders in an international environment.
- Comfortable working autonomously in a fast-moving environment and taking ownership from problem definition through production delivery and user adoption.
Additional Skills
- Experience using Python for data analysis, automation, or pipeline development is a plus.
- Experience with embedded analytics or customer-facing data products is a plus.
- Familiarity with AI-powered analytics, AI development tools, or MCP integrations is a plus.
- Experience in aviation, transportation, logistics, or another operationally complex industry is a plus.