Analytics Engineer

• Serás el vínculo estratégico entre la ingeniería de datos y la analítica de negocio
• Diseñar, mantener y monitorear modelos de datos analíticos orientados al negocio
• Construir y optimizar pipelines de transformación
• Gestionar la gobernanza integral de datos analíticos
• Colaborar con stakeholders técnicos y de negocio
• Modernizar y optimizar procesos de BI legacy
• Gestionar SLAs de disponibilidad de datos críticos

• Design and build key features and architectural improvements end-to-end — from technical discovery and system design through implementation, testing, and production support.
• Write production code daily in critical services, pipelines, and frameworks, using modern cloud-native patterns and technologies.
• Provide mentorship to the other developers on your team through design reviews, pair programming, and code reviews.
• Build deep expertise in the technology and architecture powering the Data Analytics Platform and use that knowledge to drive sound technical decisions.
• Collaborate with Product and Engineering to disambiguate requirements, surface technical uncertainty, and clearly communicate trade-offs and risks.
• Champion engineering excellence by keeping trunk/master green, stable, and deployable through strong CI/CD, testing, and operational practices.
• Coordinate with DevOps/CloudOps teams to ensure your squad has the tooling, infrastructure, and support needed to ship confidently.
• Own production reliability for the systems your squad manages, driving continuous improvement through post-mortems and root cause analysis.
• Provide 24/7 production support for the systems your team manages, driving continuous improvement in this area through post-mortems and root cause analysis.

Senior Software Developer – Data Analytics

• Actively engage with business stakeholders to understand context, challenges, and underlying needs; translate complex requirements into clear, detailed technical specifications that enable effective use of AI and analytics platforms.
• Take full responsibility for the data products you build — from ingestion through modeling, transformation, validation, to final delivery and ongoing monitoring.
• Implement and maintain rigorous validation processes, automated testing, and quality checks; act as guardian of data accuracy and integrity, ensuring metrics and KPIs accurately reflect business reality.
• Design and implement data transformation layers that pre-aggregate business information, apply consistent business rules, and deliver datasets ready for consumption in dashboards and AI applications.
• Collaborate with AI teams to specify and prepare structured data, data dictionaries, and models that enable AI platforms and intelligent reporting capabilities.
• Build and maintain data ingestion pipelines from multiple sources, implement transformations in SQL and Python, and ensure performance and scalability of solutions.
• Go beyond fulfilling requirements — proactively identify improvement opportunities, anticipate internal customer needs, propose innovative solutions, and challenge approaches when necessary.
• Deliver reliable data solutions with speed and precision, balancing the need for rapid iteration with the highest quality standards.
• Articulate technical concepts clearly to non-technical audiences; facilitate alignments, present solution proposals, and document modeling and architecture decisions.

Senior Data Developer, Analytics Engineer

• Design, build, and maintain scalable data models in Amazon Redshift to support reporting, dashboards, and ad hoc analysis.
• Collaborate with data engineering teams to expand and optimize the analytics warehouse architecture.
• Establish and enforce standards for schema design, naming conventions, and data lineage.
• Develop, maintain, and optimize data pipelines that deliver clean and reliable data to business users.
• Partner with stakeholders to gather requirements and translate business needs into scalable data solutions.
• Create and maintain comprehensive data documentation, including metrics definitions and transformation logic.
• Support BI platforms by ensuring analytics-ready datasets and assisting with dashboard development.
• Monitor data quality and implement testing, alerting, and validation processes to ensure warehouse reliability.
• Identify opportunities to improve data accessibility, consistency, and usability across the organization.
• Promote best practices in analytics engineering, including version control, code reviews, and reproducible workflows.

Analytics Engineer – Digital Media

• Participate in vendor scoping sessions to finalize full table and field requirements before the build phase begins.
• Model a dedicated datamart in the dbt transformations marts layer, sourcing data from core order, line item, and customer tables.
• Translate vendor schema specifications into specific internal field mappings, accurately accounting for DTC-adjusted logic such as ship-to addresses, order dates, and customer grain.
• Configure Snowflake data sharing and connections to facilitate seamless vendor ingestion.
• Write comprehensive dbt tests and documentation for all delivered models to ensure long-term data quality and transparency.
• Manage the full merge request workflow using GitLab, adhering to strict peer review processes before deployment.

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