Top Data Engineer Jobs in Tijuana

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.

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.

Build and maintain secure, scalable data infrastructure and pipelines using modern data tools. Implement orchestration (Airflow), transformations (DBT), and CI/CD/Infrastructure as Code. Collaborate with cross-functional teams, improve platform reliability, and document best practices to deliver high-quality data for analysis and reporting.

Build secure, scalable data infrastructure and pipelines; design and implement data orchestration and transformation solutions with Airflow/DBT/Snowflake; ensure high-quality data delivery for analysis and reporting; automate deployments with IaC; improve observability; document best practices; support DataOps initiatives. Hybrid role in Mexico City (twice weekly onsite).

Lead design and delivery of scalable ETL/ELT pipelines into Snowflake, build dbt-based semantic models and metric definitions, use Databricks/PySpark for high-scale transformations, manage AWS-based data infrastructure, implement data quality, monitoring, and governance to create authoritative data marts.

Senior Data Engineer responsible for designing and optimizing scalable Snowflake and dbt pipelines to handle billions of rows. Improve performance, storage, query execution, and cost efficiency; migrate/refine legacy processes; troubleshoot bottlenecks; provide technical leadership, mentorship, and documentation.

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.

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.

Lead design and delivery of Azure-based data platforms and Lakehouse architectures (Microsoft Fabric, Azure SQL, Power BI). Build scalable ETL/ELT pipelines, medallion-layered models, and AI-ready data feeds (embeddings/feature stores). Drive migrations from legacy systems, enforce governance and PII protection, mentor engineers, perform code reviews, optimize performance, and collaborate with product and business stakeholders to deploy analytics and reporting solutions.

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.

Lead data quality and test automation for the enterprise data lake. Architect end-to-end testing frameworks across APIs, UI, and data pipelines; design data profiling and monitoring systems; use LLMs to accelerate test generation and engineering tasks; build internal automation tools and dashboards; ensure high-quality, compliant data products in cloud and distributed environments.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.

Design, build, and maintain scalable Airflow-based data pipelines and reusable components. Implement CI/CD for deployments, enforce data governance and quality, monitor and troubleshoot workflows, document solutions, and mentor teammates on Airflow best practices.

The Staff Engineer, Data Science role focuses on leveraging tech skills to enhance team capabilities and provide advanced solutions for client challenges.

Lead technical migration from on-prem Oracle and Boomi to Azure SQL and Azure Data Factory. Provide architecture and design guidance, coordinate database and ETL workstreams, act as client technical contact, manage timelines/risks/deliverables, validate source-to-target mappings, support cutover and post-migration stabilization, and maintain technical documentation and best practices.

Lead evaluation and benchmarking of enterprise-scale graph databases. Extract, transform, and load data from Databricks into multiple graph platforms, implement benchmark workloads and APIs, analyze query plans and indexing, provision test environments, document results, and advise architects and leaders on technical trade-offs and recommendations.

Design, build, and maintain scalable data and ML pipelines, manage vector stores and RAG workflows, integrate LLM frameworks for training and inference, enable semantic search and AI-driven BI, and document data processes while partnering with stakeholders.

Design and maintain data pipelines, optimize data processing with PySpark on Databricks, ensure data quality, and collaborate on data architecture solutions.

Design and maintain end-to-end data pipelines using Microsoft Fabric and Azure Synapse, ensuring data quality and performance optimization while collaborating with cross-functional teams.

Drive quality assurance strategy for data migration projects, validating data integrity and automation using AWS technologies and Python scripts.

The role involves designing and maintaining data pipelines, developing ETL/ELT processes, building Power BI dashboards, and ensuring data quality and governance.

Design, build, and maintain batch and real-time ETL/ELT data pipelines and workflows. Collaborate with US-based stakeholders to translate requirements into technical solutions, implement code, ensure data quality, logging, security, and compliance, and mentor other data engineers. Work with cloud data warehouses, data lakes, big data technologies, visualization tools, and pipeline orchestration frameworks.

Design, build, and maintain scalable and reliable data pipelines, implementing ETL workflows and optimizing Snowflake solutions, while collaborating with data scientists and engineers.

Design, build, and scale cloud-based data pipelines and reporting infrastructure for advertising performance and billing reconciliation. Ensure data quality, secure handling of financial data and PII, modernize legacy SQL Server ETL, implement IaC and CI/CD, and collaborate with Product, Engineering, Analytics, and business stakeholders to enable reliable, automated data consumption.