The Opportunity
The Senior Data Engineer – Data Operations is responsible for ensuring the reliability, availability, and operational excellence of the LATAM Data Hub platform across Latin America. This role plays a critical part in supporting enterprise data solutions that enable reporting, analytics, and data delivery to business and digital channels across the region. Based on the standard job posting template in this section highlights the role’s overarching impact and candidate value proposition.
Guided by our purpose—always with you, building a more confident future—and our New Frontier growth strategy, this is an exciting opportunity to work with modern cloud and data technologies while helping maintain and enhance a large-scale data ecosystem. You will contribute to the stability of business-critical data platforms, collaborate with teams across multiple countries, and influence the evolution of monitoring, automation, observability, and AI-driven operational capabilities.
Key Responsibilities
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Monitor and support the daily operation of enterprise data pipelines, workflows, and platform services to ensure reliable data delivery.
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Investigate, troubleshoot, and resolve production issues impacting data ingestion, processing, storage, and consumption.
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Manage incident response activities, perform data validation and quality checks, and coordinate escalations when necessary.
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Develop and maintain operational documentation, monitoring solutions, dashboards, alerts, and automation capabilities that improve platform observability and efficiency.
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Partner with Data Engineering, DevOps, Solution Engineering, and business teams to support deployments, production releases, and continuous improvement initiatives.
Required Qualifications
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Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
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5+ years of experience supporting or developing enterprise data platforms, ETL solutions, or data warehousing environments in production.
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Strong experience with cloud-based data technologies, preferably within Microsoft Azure, including platforms such as Azure Synapse, Databricks, Data Lake Storage, Cosmos DB, and related data services.
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Advanced knowledge of SQL and Python, with demonstrated experience analyzing data, identifying anomalies, and resolving data pipeline issues.
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Strong problem-solving, communication, and collaboration skills, with the ability to work effectively across technical and non-technical teams.
Preferred Qualifications
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Experience with Terraform or similar Infrastructure-as-Code tools for scalable cloud infrastructure management.
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Familiarity with containerized applications, DevOps practices, CI/CD pipelines, and monitoring or observability platforms.
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Working knowledge of English and experience supporting business-critical systems in a 24x7 operational environment.
