Top Data Engineer Jobs in Mexico

Design, build, and operationalize scalable data solutions for customers; support data ingestion, transformation, quality, governance, and analytics to enable AI/ML and BI. Troubleshoot, test pipelines, collaborate with teams, and guide customers on technical decisions.

As a Data Engineer, you will build and maintain data platforms, ensuring high-quality data availability for decision-makers, and develop ETL/ELT processes while utilizing data modeling techniques.

Build and maintain data models, dashboards, reports, and dbt models supporting cross-functional decision-making. Process large datasets, establish reporting sources of truth, bridge technical and business teams, and document knowledge bases and business definitions for internal AI systems. The role also involves identifying cost-saving opportunities, communicating with stakeholders, and using AI to develop solutions and fix bugs.

Build production LLM agents, multi-step workflows, MCP servers, evaluation and observability systems, and document-extraction pipelines. Architect AI-ready semantic data layers over Snowflake and dbt, develop Python ingestion and Airflow workloads, and implement retrieval, embeddings, governance, security, and reliable agent operations. Lead technical design, mentor peers, and advise clients in an embedded consulting engagement.

The Senior Software Engineer will design and operate data ingestion and processing systems for multimodal data, ensuring quality, security, and compliance while optimizing for performance and reliability. Responsibilities include building pipelines, handling messy data, and partnering with teams to enhance the platform's capabilities.

The Staff Engineer will define architecture, lead data pipeline design, ensure platform reliability, and mentor engineers, driving data initiatives and technical standards.

As a Senior Data Engineer, you will design, build, and maintain scalable data platforms, ETL pipelines, and support analytics and ML workflows, ensuring data quality and cross-functional collaboration.

Design and build self-service analytics portals and responsive dashboards. Integrate data pipelines from Databricks, S3, Salesforce and internal APIs. Implement secure auth and role-based access. Collaborate with product and data teams, remain hands-on, and mentor junior developers to deliver scalable, customer-facing analytics experiences.

The Senior Data Engineer will design and maintain ETL pipelines, automate report generation, and ensure data quality while collaborating with various teams.

Design, build, and maintain scalable data pipelines, vector stores, feature stores, and LLM-driven workflows. Implement RAG, prompt engineering, model fine-tuning, and managed LLM deployments on cloud. Optimize big-data processing, enable real-time inference, build analytics/NL query dashboards, document processes, and partner with stakeholders to translate requirements into production BI/ML solutions.

Build and maintain data pipelines, dbt transformations, SQL models, and analytics datasets. Develop Power BI dashboards, semantic models, and DAX measures while validating data quality and troubleshooting issues end to end. Translate business needs into reporting solutions, support existing analytics environments, and independently deliver production-ready work. Collaborate with business, analytics, and engineering teams while applying AI tools to improve productivity.

Design and implement AI-powered data pipelines and production workflows using LLMs, automation, and modern data engineering. Build systems that extract, clean, enrich, validate, and transform structured and unstructured data into customer-ready Excel, PDF, and Word outputs. Develop APIs and full-stack applications, optimize relational and vector databases, integrate AI orchestration frameworks, and translate prototypes into scalable enterprise solutions.

Designs, develops, and supports software applications, databases, reporting solutions, and automated workflows. Responsibilities include SQL development, SQL Server-to-Databricks migration, Power BI dashboard and semantic model optimization, DAX development, Power Automate maintenance, data quality analysis, production troubleshooting, SSL certificate management, stakeholder collaboration, and architecture reviews. The role also evaluates AI technologies and supports adoption across reporting, automation, and software delivery.

Lead design and delivery of Snowflake-based data ingestion and ELT pipelines, enforce Medallion Architecture and data quality frameworks, build/optimize AWS data pipelines, drive governance, mentor teams, and act as a client-facing technical leader ensuring reliable, governed data for analytics.

Lead design and implement standardized ETL pipelines, data transformations, and data quality frameworks to migrate and unify data from 80+ ERP systems into Microsoft Fabric. Conduct gap analyses, build AI-ready data models, run pilot implementations, troubleshoot data issues, document lineage, and mentor engineers on Fabric-specific best practices and automation for scalable analytics workloads.

Design, build, and maintain API integrations and data pipelines to move and activate customer data across systems. Implement identity resolution, ensure data quality and secure handling of identifiers, troubleshoot integrations, and collaborate with engineering, data, and business teams to deliver scalable CDP-related solutions.

Design, build, and maintain scalable ETL pipelines and automated reports using Python, dbt, Airflow, and Snowflake. Own production pipelines, monitor performance, troubleshoot data issues, and partner with analytics and product teams to deliver end-to-end data solutions for financial use cases.

As a Software Engineer, you'll design, build, and maintain data platform products, ensuring operational excellence and high availability while collaborating with internal teams and contributing to open-source tools.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

Senior UI developer responsible for designing and building responsive React-based UIs and dashboards for cybersecurity analytics. Develop backend services and APIs in Python, integrate security data sources, optimize SQL Server/PostgreSQL reporting, collaborate with stakeholders, influence architecture, and mentor junior developers.

The Data Quality Engineer ensures the quality and integrity of data in studies, developing measurement systems, automation, and conducting analysis to uphold standards across projects.

Design, build, and maintain production-grade data pipelines and models to power AI/ML workloads. Own pipeline reliability (orchestration, monitoring, incident response), collaborate with product and engineering to define requirements, optimize performance and cost, and document data models and runbooks.

Lead design and implementation of an enterprise data quality framework using Great Expectations, creating Rule-as-Code validations, observability, lineage, CI/CD integration, dashboards, and remediation processes while collaborating with cross-functional teams to prevent and resolve data issues.

Senior integration engineer responsible for designing and implementing API integrations, ETL pipelines, and Power Platform connections; building and maintaining APIs and data transformation workflows; ensuring data quality, security, reliability, and optimizing/troubleshooting integration flows.

Monitor daily data intake across API, email, and FTP channels; perform QA to detect inconsistencies or trends; resolve data pipeline issues; document findings and follow procedures; and propose process/product improvements while working shift-based hours.