Azure data engineer

Remote position in México

Data Engineer

Role Overview

The Data Engineer is responsible for designing, building, and maintaining scalable, cloud native data pipelines and data infrastructure that support analytics, reporting, business intelligence, and real-time data processing.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for batch and real-time
  
  

data processing.

• Build and optimize data models, Delta Tables, and Lakehouse architectures to
  
  

support analytics and reporting.

• Develop and integrate RESTful APIs and data services to facilitate seamless data
  
  

exchange across enterprise systems.

• Implement real-time and high-frequency data ingestion frameworks using streaming
  
  

technologies and event-driven architectures.

• Design and manage cloud-native data solutions leveraging Azure services including
  
  

Azure Data Factory, Azure Databricks, ADLS, Event Hubs, and Synapse Analytics.

• Develop and optimize Databricks Spark applications for large-scale data
  
  

transformation and processing.

• Ensure data quality, governance, security, and compliance across data platforms.
• Collaborate with data scientists, analysts, application teams, and business
  
  

stakeholders to deliver scalable data solutions.

• Troubleshoot, monitor, and optimize pipeline performance and data platform
  
  

reliability.

• Support DataOps and CI/CD practices for data pipeline deployment and
  
  

automation.

Required Skills & Qualifications

• Strong proficiency in SQL and relational databases such as Oracle, SQL Server, and
  
  

MySQL.

• Strong programming skills in Python, PySpark, PL/SQL, Java, or Scala.
• Hands-on experience with Azure Cloud technologies:
• Azure Data Factory (ADF)
• Azure Databricks
• Azure Data Lake Storage (ADLS)
• Azure Synapse Analytics
• Azure Event Hubs
• Azure Functions
• Azure API Management
• Azure DevOps
• Experience with Databricks Lakehouse architecture, Delta Lake, and Delta Tables.
• Expertise in API development, API integration, RESTful services, and microservices
  
  

architecture.

• Experience processing high-volume and high-frequency data with low-latency
  
  

requirements.

• Strong knowledge of real-time data ingestion and streaming technologies such as
  
  

Kafka, Azure Event Hubs, or Kinesis.

• Experience with Spark, Hadoop, and distributed data processing frameworks.
• Hands-on experience with OpenShift, Kubernetes, Docker, and containerized
  
  

deployments.

• Experience with workflow orchestration tools such as Apache Airflow and Azure
  
  

Data Factory.

• Understanding of data governance, data security, and compliance best practices.
  
  

Preferred Qualifications

• Experience with Delta Live Tables (DLT), Auto Loader, and Change Data Capture
  
  

(CDC).

• Knowledge of DataOps, CI/CD, and Infrastructure as Code (IaC).
• Familiarity with event-driven architectures and real-time analytics platforms.
• Azure Data Engineer (DP-203) and Databricks certifications
  
  

mandatory skills:

• Python
• Azure
• SQL
  
  

REMOTE

ADVANCED ENGLISH