Top Data Engineer Jobs in Tijuana

Build and maintain scalable data pipelines, ETL/ELT processes, data models, metric definitions, and data infrastructure. Develop production solutions with Python, SQL, Spark, dbt, Fivetran, Airflow, Databricks, Azure, and cloud storage. Collaborate with data scientists, engineers, analysts, and stakeholders to deliver reliable, accessible data and self-service tools. Troubleshoot pipeline issues, improve data quality and scalability, and use AI-assisted development tools to accelerate engineering work.

Designs and operates scalable data architectures, pipelines, ETL processes, databases, warehouses, and lakes. Improves data quality, governance, observability, security, and reliability while partnering with stakeholders to develop effective data solutions. Provides technical leadership, mentors engineers, leads code reviews and cross-functional initiatives, resolves production issues, and drives improvements to engineering platforms and practices.

Leads the design, development, deployment, and maintenance of data pipelines and analytics platforms using Microsoft Fabric and Azure. Builds Lakehouse and Warehouse solutions, develops transformations with SQL, Python, and PySpark, and ensures data quality, security, performance, and governance. Collaborates with architects, developers, analysts, and stakeholders in Agile teams, contributes to CI/CD and documentation, leads technical discussions, mentors junior engineers, and provides technical guidance across client engagements.

Designs, builds, and maintains large-scale data pipelines using Databricks, PySpark, and Apache Spark. Develops ETL/ELT processes, lakehouse architectures, and optimized data workflows while ensuring quality, reliability, performance, and observability. Collaborates with architects, analysts, and stakeholders to deliver scalable data solutions. Uses orchestration, version control, CI/CD, and automation practices to support modern analytics platforms.

Lead the design and implementation of scalable on-premises and cloud data platforms. Build and maintain ETL/ELT pipelines, support data governance and quality, participate in architecture and planning, and mentor engineers through code reviews and technical guidance. The role requires strong Python, Spark, Hadoop, SQL, Databricks, orchestration, DevOps, and CI/CD expertise, along with effective communication in English and Spanish.

Build and maintain large-scale ETL/ELT pipelines using Databricks, Spark, Python, Hadoop, and cloud data platforms. Develop and optimize PySpark data processing jobs, improve pipeline performance and cost, and support CI/CD, testing, deployment automation, and observability. Collaborate with Product Managers to define user-focused data modules and features. Debug complex data issues and communicate effectively with technical and non-technical stakeholders.

Builds the data and knowledge infrastructure powering AI agents, including production RAG pipelines, embeddings, vector search, reranking, ingestion, ETL/ELT, document processing, and knowledge architecture. Integrates Salesforce, ServiceNow, enterprise repositories, PostgreSQL, vector stores, and Snowflake while ensuring data quality, security, lineage, scalability, and retrieval performance. Develops multi-tenant indexing and feedback systems and collaborates with GenAI engineers in a remote Brazil-based role requiring fluent English and occasional travel.

Designs and maintains scalable batch and real-time ETL/ELT pipelines, data models, Lakehouse architectures, APIs, and streaming frameworks. Builds Azure- and Databricks-based data solutions using Spark, Delta Lake, and related services. Ensures data quality, governance, security, compliance, and platform reliability while supporting DataOps, CI/CD, monitoring, and performance optimization. Collaborates with data scientists, analysts, application teams, and stakeholders on enterprise data solutions.

Design, build, and optimize large-scale data pipelines using Databricks, PySpark, ETL/ELT, and lakehouse architectures. Ensure data quality, reliability, performance, and observability while applying Spark optimization techniques. Collaborate with architects, analysts, and stakeholders to deliver scalable data solutions. Implement CI/CD, version control, workflow orchestration, and automation using tools such as Azure Data Factory, Airflow, or Fabric. Communicate technical solutions effectively across technical and non-technical teams.

Build and maintain scalable batch and streaming data pipelines, develop and optimize data models in a cloud warehouse, implement ELT/ETL and orchestration (Airflow/Dagster), ensure data quality and monitoring, handle sensitive data with HIPAA-aligned practices, and evolve the platform's data architecture while partnering with analytics, product, and engineering teams.

Build and maintain end-to-end data pipelines, models, data marts, and semantic layers supporting agency, client, BI, product, and AI consumers. Integrate fragmented marketing and customer data across advertising platforms, e-commerce, analytics, and CRM systems. Manage dbt projects, multi-tenant Snowflake infrastructure, data quality, performance, and client-specific modeling. Use AI coding agents, cloud infrastructure, CI/CD, and automated testing while collaborating across product, engineering, analytics, and client teams.

Develops data-driven solutions for finance, accounting, and regulatory reporting. Automates reconciliations, builds self-service data tools, creates dashboards and metrics, analyzes business strategies, and monitors data quality. Partners with finance, business, and technology teams to translate requirements into technical solutions while supporting data governance, security, access controls, metadata, lineage, and compliance.

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.

Design, build, and operationalize scalable data solutions and pipelines for customers. Analyze and transform data, ensure data quality/governance/security, test data movements, troubleshoot incidents, and collaborate with teams to support AI/ML and BI use cases.

Designs, builds, deploys, and operationalizes complex data engineering solutions for multiple customers. Responsibilities include Databricks migrations, data pipeline development, transformations, optimization, governance, security, quality, testing, incident resolution, and data source analysis. The role also involves advising customers, tracking project progress, collaborating across teams, and educating users on data products and analytics environments.

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.

The Data Architect role involves defining the data strategy, optimizing data schemas, enhancing performance, and collaborating with multiple teams for effective data management.

The Data Engineer I will design and manage data pipelines, integrate ETL processes, ensure data quality, and optimize performance while working with various cloud and on-premises technologies.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Design, build, and optimize scalable data pipelines and storage on Azure (data lakes/warehouses). Integrate and transform data from databases, APIs, and streaming sources; tune performance; collaborate with data scientists and stakeholders; work in Agile; mentor junior engineers and deliver robust, production-ready solutions with CI/CD practices.

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.

Senior AWS Data Engineer to design and operate AWS-based data solutions and Snowflake-centric platforms. Build data pipelines, implement Snowflake AI components, design data marts/warehouses/lakes, produce architecture drafts, and collaborate with architects and stakeholders for handoff to operations.

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.

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.