Top Data Engineer Jobs in Leon

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 develop and maintain ETL processes using Python and Azure Synapse Analytics, ensuring data integration accuracy and performance. Responsibilities include data warehousing design, performance tuning, collaboration with teams, and maintaining data quality and documentation.

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

Designs, builds, and monitors scalable data pipelines and storage to support marketing models. Implements data transformations, data modeling, and quality assurance using SQL, Python, and modern data stack tools. Collaborates with analysts, data scientists, and stakeholders and enforces data governance and security compliance.

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 Azure Data Engineer will participate in the software development lifecycle, including design, coding, testing, and documentation of applications, collaborating closely with team members and following best practices.

Lead AWS Data Engineer responsible for designing and implementing cloud-native data solutions, overseeing data migrations, and mentoring engineering teams.

As an AI Data Engineer, you will build end-to-end data pipelines, collaborate on AI features, and ensure data quality across our systems.

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, deploy, and operate scalable cloud-based data and analytics solutions. Integrate AI services (Azure OpenAI, Cognitive Services), implement monitoring, collaborate cross-functionally, and apply engineering best practices across end-to-end systems.

The role involves understanding customer processes, validating technical designs of applications, estimating project efforts, supporting implementation activities, and mentoring colleagues in application architecture.

Lead design, development, and optimization of cloud-native data platforms and ETL/ELT pipelines. Architect data models, enforce engineering best practices, implement orchestration (Airflow/dbt), monitoring, and data quality frameworks. Mentor engineers, drive architectural decisions, ensure security and governance, and support analytics and machine learning initiatives across teams.

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.

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, 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.

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

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 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.

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.