We are looking for a highly experienced, hands-on Senior Data Engineer who can combine deep data engineering expertise with data architecture, cloud platform ownership, and direct client engagement.This is not a traditional back-office data engineering role where you own one pipeline or a narrow piece of a larger platform. You will work directly with clients to understand their needs, recommend the right technical approach, design the architecture, build the solution, and communicate the results.You will typically own multiple client projects and operate as both the technical expert and a trusted advisor. The right person is comfortable running a client meeting, discussing architectural trade-offs with technical and business stakeholders, turning those decisions into working solutions, and owning delivery from beginning to end.We are especially interested in engineers who have worked in consulting, startups, or other environments where they have had broad ownership rather than operating within one narrow function of a large data organization.ResponsibilitiesOwn the technical delivery of data projects from initial client conversations through architecture, implementation, and ongoing deliveryLead client discussions to understand business and technical requirements, ask the right questions, and translate ambiguous problems into clear technical solutionsDesign modern data architectures spanning ingestion, transformation, compute, storage, analytics, and BI layersMake informed architecture recommendations based on technical trade-offs, cost, scalability, maintainability, and the client's specific requirementsBuild and maintain production data pipelines, transformations, models, and platform componentsWork hands-on with modern data platforms such as Snowflake, Databricks, BigQuery,



and/or RedshiftBuild and maintain transformation workflows using SQL and modern data tooling such as dbtWork directly within AWS, GCP, and/or Azure environments, including platform deployment, infrastructure configuration, access and permissioning, and related cloud resourcesTake end-to-end ownership rather than relying on separate infrastructure, architecture, or project-management teams to drive deliveryManage multiple client projects simultaneously while maintaining clear priorities, timelines, documentation, and follow-upProduce polished client-facing documentation, presentations, meeting notes, and project updatesCollaborate with software and AI engineers on a proprietary platform deployed into customer cloud environmentsContribute code and improvements to platform capabilities when neededUse AI tools extensively to accelerate engineering, research, analysis, and development while maintaining a strong understanding of the underlying technical decisionsRequirements 5+ years of professional, hands-on data engineering experience, ideally with significant senior-level ownershipAdvanced SQL skillsStrong hands-on experience with at least one modern cloud data platform such as Snowflake, Databricks, BigQuery, or Redshift; experience across multiple platforms is highly valuedStrong understanding of data architecture and data modeling principles, including common design patterns, anti-patterns,



and architectural trade-offsExperience designing data environments across ingestion, compute, storage, transformation, and analytics/BI layersHands-on cloud experience with AWS, GCP, and/or Azure beyond simply consuming cloud-hosted servicesExperience deploying or owning data platforms and working with infrastructure configuration, access controls, permissions, compute resources, and cloud architectureExperience making technical architecture decisions and clearly explaining the reasoning and trade-offs behind those decisionsExcellent spoken and written EnglishStrong client-facing or stakeholder-facing communication skills, with the confidence to lead technical discussions with senior stakeholders and executivesAbility to communicate complex technical topics concisely and focus conversations on what mattersCuriosity about AI and a strong understanding of how AI is changing modern data infrastructure, analytics, and data consumption PreferredSignificant hands-on experience with dbtExperience working as a Data Engineering Consultant, Data Consultant, Data Architect, Solutions Architect, or similar client-facing technical roleExperience working in startups, consultancies, or other lean environments requiring broad technical ownershipExperience owning or managing a complete data or analytics platformExperience across two or more of Snowflake, Databricks, BigQuery, and RedshiftStrong understanding of cloud infrastructure, platform deployment, access management, and infrastructure cost considerationsPrevious software engineering experience before moving into data engineeringFamiliarity with emerging AI/data infrastructure concepts, including MCP and AI-oriented data workflowsBenefitsSalary: $90K to 120K USD annually based on experiencePTO: 15 days Holidays: Local or US holidays

📌 Senior Data, Platform & Solutions Engineer (Ciudad de México)
🏢 SUR
📍 Ciudad de México