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: o Azure Data Factory (ADF) o Azure Databricks o Azure Data Lake Storage (ADLS) o Azure Synapse Analytics o Azure Event Hubs o Azure Functions o Azure API Management o 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 Originally posted on Himalayas