Client: Our client is a leading airline group in Latin America, driving the digital transformation of its air cargo business and committed to data-driven decision-making across its operations.
Project overview: This project supports the digital transformation of an air cargo business through a data driven approach across operations. The team builds and maintains scalable, governed data solutions on Google Cloud Platform to ensure information flows reliably from generation to consumption.
Position overview: We are looking for a Senior Data Engineer to act as a technical referent within the data chapter. You will combine hands on delivery with technical leadership, guiding architecture decisions, resolving complex problems end to end, and supporting peers through mentoring and knowledge transfer without formal people management responsibilities.
Technology stack: Google Cloud Platform, BigQuery, Dataform, Cloud Run, Pub/Sub, Cloud Storage, Dataflow, CloudSQL, SQL, Python, Git, GitLab, CI/CD, Terraform, IAM, Policy Tags, MCP, prompt engineering, Looker Studio, Google Data Studio, Grafana, Agile, DataOps
- Responsibilities: Define and steer the team's data engineering strategy, connecting it to product and business needs.
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Act as a technical referent, orienting decisions and solving complex data problems end to end.
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Lead technically and influence the team, turning strategy into shared criteria and agreements.
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Design, build, and maintain robust, scalable pipelines and models on Google Cloud Platform, including BigQuery, Dataform, Pub/Sub, and Cloud Run.
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Ensure the coherence, quality, security, governance, and sustainability of the team's solutions.
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Stay hands on in the design and construction of high impact solutions.
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Represent the data perspective in squad decisions and keep alignment with capability guidelines.
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Support the team's technical growth through mentoring, feedback, and knowledge transfer.
- Requirements: Solid, proven experience as a Senior Data Engineer designing, building, and evolving complex, scalable, and sustainable data solutions.
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Strong SQL and Python, including query optimization on cloud data platforms.
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Hands on experience with Google Cloud Platform, including BigQuery, Dataform, Cloud Run, Cloud Storage, Pub/Sub, Dataflow, and CloudSQL.
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Experience with end to end data architecture and modeling, including Medallion architecture, integration and processing, with quality, governance, security, and observability.
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Ability to define technical direction by weighing alternatives, risks, dependencies, technical debt, and trade offs.
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Experience with engineering best practices, including Git, GitLab, CI/CD, and Infrastructure as Code with Terraform.
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Experience with IAM and Policy Tags for security and governance.
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Experience with data governance, compliance, and documentation practices.
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Experience mentoring engineers and articulating technical decisions to technical and business stakeholders.
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Fluency in Spanish and intermediate English for documentation and international collaboration.
- Nice to have: Experience with AI, automation, and agentic systems applied to data solutions, including MCP and prompt engineering.
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Experience with visualization using Looker Studio or Google Data Studio.
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Experience with monitoring using Grafana.
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Experience working in Agile environments.
