Top Data Engineer Jobs in Mexico City

As a Data Engineer, you will design and build scalable analytics pipelines, manage data integrations, and optimize data architecture for large-scale projects.

As an ETL Data Engineer, you will design, develop, and maintain data integration processes, ensuring data accuracy for insights. Collaboration with data scientists and analysts is key, involving data warehousing, performance tuning, and ETL documentation.

As an ETL Data Engineer, you'll design and maintain data integration processes using Python and Azure Synapse Analytics, collaborating with data teams to ensure data quality and performance optimization.

Lead AI engineering on the Data Platform: build Databricks Apps deployment paths, construct an AI layer over the Medallion Architecture and semantic layer, enable LLM/NLP systems and agentic workflows, embed AI tooling in the developer lifecycle, enforce guardrails for production safety, define metadata/modeling patterns, and mentor engineers to accelerate AI adoption.

Design, build, and deploy scalable data lakehouse and warehouse platforms; implement and optimize ETL/ELT pipelines (Databricks, dbt); develop data models and Medallion architecture layers; manage CI/CD and Infrastructure as Code (Azure DevOps, Terraform, CloudFormation); use cloud-native serverless offerings across major clouds; ensure data security and governance; integrate pipelines with BI tools like Tableau, Looker, and Power BI; communicate technical designs to stakeholders.

Design and build multi-tenant backend and data foundations: PostgreSQL schemas with RLS, async Python services (FastAPI), OpenAPI-first contracts, and orchestrated data pipelines for secure, scalable AI platforms.

The Staff Data Engineer will lead data model design, standardize data engineering practices, modernize orchestration, and establish governance strategies within Dropbox's Analytics team.

Design, build, and maintain scalable ETL/ELT pipelines and data architecture; integrate multiple data sources; ensure data quality, governance, security, and performance; monitor pipelines; support BI, analytics, and ML; document models and workflows; collaborate with stakeholders.

Manage the Databricks environment, implement data governance, oversee data architecture in Snowflake, and handle data pipelines across cloud platforms.

Design, architect, and operate an agentic data engineering ecosystem: build and govern autonomous agents for ETL, synthetic data, QA, and modeling; integrate secure context via MCP servers to Snowflake, Salesforce, and AWS; validate agent outputs and translate ambiguous business requests into production data products.

Design, build, and optimize Azure-based data pipelines and storage (data lakes/warehouses). Transform and model large datasets, tune performance, and collaborate with data scientists and stakeholders. Mentor junior engineers and deliver solutions within Agile/Scrum processes.

Design, model, and develop the GCP data ecosystem (Cloud Storage, Cloud Functions, BigQuery). Build and optimize data pipelines, data storage architectures, and query performance. Troubleshoot high-impact issues, monitor system performance, and mentor junior engineers. Engage directly with clients and document business/technical requirements.

The Data Engineer will design and maintain scalable ETL/ELT pipelines on Databricks and AWS, optimizing data infrastructure for gaming analytics and decision-making.

Design and build scalable Databricks-based data and GenAI pipelines, implement RAG/vector search, integrate LLMs for enrichment and anomaly detection, create natural-language data interfaces, ensure data quality and traceability, and support CI/CD automation across analytics and engineering teams.

Hands-on Senior Data Engineer to design and maintain scalable AWS ETL/ELT pipelines, evolve a data lakehouse with Apache Iceberg, implement governance and security, optimize performance and costs, enable analytics-ready datasets, and ensure reliability, monitoring, and data quality.

Design, build, and optimize ETL/ELT pipelines to ingest Salesforce and Jira into Snowflake; implement transformations, data quality checks, monitoring, and governance; collaborate with Power BI developers, admins, and analysts; produce technical documentation and participate in Agile delivery.

Design, build, and scale data pipelines and analytics solutions across the full data lifecycle. Implement ETL, data modeling, and high-volume data systems using Spark/Scala, Python, Databricks, Airflow, and AWS. Collaborate with stakeholders, contribute to architecture and CI/CD practices, and deliver projects on schedule.

Build, monitor, and troubleshoot data pipelines and transformations for healthcare data. Extract, cleanse, and load data; implement data quality checks; document datasets; support API and EFT integrations; triage incidents; and participate in Agile ceremonies to estimate and deliver data solutions.

The Senior Databricks Engineer will design, build, and maintain scalable data pipelines, optimize ETL/ELT processes, and ensure data quality and governance while collaborating with teams to meet data requirements.

The Data Engineer is responsible for designing and maintaining data pipelines and infrastructure, ensuring data accessibility and quality for analytics and reporting.

Analyze existing integrations and rebuild ETL/ELT pipelines in Azure Data Factory. Design, develop, schedule, monitor, and optimize data movement and transformations. Connect ADF to sources/targets (Oracle, Azure SQL, files, APIs), implement parameterization, retry logic, and alerting. Perform mapping, validation, testing, documentation, deployments, and production cutover while collaborating with database engineers, QA, architects, and business teams.

Responsible for managing data acquisition, curation, and publishing for analytics, developing data products, and creating scalable data pipelines.

Build and own core data pipelines and models for Lyft's Safety and Customer Care platform. Scale data processing, tune SQL/MapReduce jobs, implement data quality systems, develop ETL self-service tools, and collaborate cross-functionally to deliver accurate reporting and analytics.

As a Data Engineer, you will enhance the US Gas product by building data scrapers, improving APIs, and collaborating on features with the product team.

Design and build scalable Snowflake-based data models, analytical cubes, and high-performance data pipelines using SQL and Python. Integrate data via APIs, collaborate with cross-functional teams to support reporting and analytics, and enforce best practices in data architecture and pipeline performance.