Client: Our client is a leading airline in Latin America, committed to innovation and delivering seamless customer experiences through cutting edge digital platforms.
Project overview: The Data and Analytics organization plays a critical role in enabling data driven decisions across the company, ensuring information flows efficiently from its generation to its consumption. The team designs and maintains scalable data pipelines and models that power analytical use cases, operational systems, and digital products across LATAM. Operating in a Google Cloud Platform (GCP) environment, the team works with tools such as BigQuery, Dataform, Python, APIs, and Terraform, following Agile and DataOps best practices to ensure reliability, scalability, and business impact.
- Position overview: We are looking for an Analytics Engineer with a strong foundation in data modeling and a clear understanding of the data lifecycle, with a focus on enabling business teams to build and operate their own data products.
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The ideal candidate combines technical expertise with business understanding, capable of translating analytical needs into scalable, well-structured, and governed data models. This role is not only hands on, but also acts as a mentor and guide, helping teams adopt best practices in analytics engineering, data governance, and data usage. The candidate acts as a connector between data engineering, analytics, and business domains, supporting the organization in evolving toward a scalable self-service data model.
- Responsibilities: Design, build, and maintain scalable data models that support analytical and business use cases.
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Understand the current “as is” state of data models and analytical needs, identifying gaps, inconsistencies, and improvement opportunities.
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Define and promote best practices in data modeling, documentation, data quality, and governance across teams.
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Translate business requirements into clear and reusable data models, collaborating closely with multidisciplinary teams (product, analytics, technology, and business).
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Support and mentor teams in the correct use of tools and frameworks such as Dataform, BigQuery, Git, and CI/CD workflows.
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Ensure consistency and alignment of business metrics and KPIs across domains.
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Collaborate with Data Engineers to ensure upstream data availability, integrity, and usability.
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Enable data consumption through BI tools and support self service analytics initiatives.
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Participate in code reviews and design reviews, ensuring adherence to standards and best practices.
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Contribute to the definition of reusable templates, guidelines, and scalable data solutions.
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Promote data governance and literacy, encouraging data informed decision making across teams.
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Actively participate in data project prioritization and planning, balancing business impact and scalability.
- 3 years of proven experience in Analytics Engineering, Data Analytics, or similar roles.
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Proficiency in SQL and BigQuery.
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Experience working with Dataform or similar data modeling frameworks (e.g., dbt).
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Strong understanding of data modeling concepts (dimensional modeling, data marts, metrics definition).
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Experience working with BI tools (e.g., Looker).
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Proficiency in Python for data analysis and exploration.
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Familiarity with GIT and CI/CD concepts.
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Understanding of data governance, data quality, and documentation practices.
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Ability to communicate effectively with both technical and non technical stakeholders.
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Experience working in Agile environments, participating in sprints and cross functional collaboration.
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Fluency in Spanish (team language) and intermediate English for documentation and international collaboration.
