Hiring: Data Engineer (Remote position)

HYR Global Source Inc is seeking a skilled Data Engineer to join their team on a 12+ months remote opportunity. The role involves designing, developing, and maintaining scalable ETL/data pipelines, ensuring data pipeline reliability, and collaborating with cross-functional teams to support reporting and analytics initiatives.

Responsibilities:

• Design, develop, and maintain scalable ETL/data pipelines in cloud environments
• Build and manage both batch and real-time (streaming) data processing workflows
• Develop and optimize data transformations using Python, SQL, and Apache Spark
• Implement robust data solutions using Databricks and Azure Data Factory
• Ensure data pipeline reliability, scalability, and performance through monitoring and optimization
• Collaborate with cross-functional teams, including analysts, BI developers, and DevOps engineers
• Support reporting and analytics initiatives by enabling clean, well-structured datasets for BI tools
• Apply best practices in data quality, testing, version control, and CI/CD automation

Requirements:

• Strong hands-on experience building scalable data pipelines
• Expertise in data processing, automation, and performance optimization across large-scale data systems
• Design, develop, and maintain scalable ETL/data pipelines in cloud environments
• Build and manage both batch and real-time (streaming) data processing workflows
• Develop and optimize data transformations using Python, SQL, and Apache Spark
• Implement robust data solutions using Databricks and Azure Data Factory
• Ensure data pipeline reliability, scalability, and performance through monitoring and optimization
• Collaborate with cross-functional teams, including analysts, BI developers, and DevOps engineers
• Support reporting and analytics initiatives by enabling clean, well-structured datasets for BI tools
• Apply best practices in data quality, testing, version control, and CI/CD automation
• Programming: Python, SQL
• Data Processing: Apache Spark, Databricks, Azure Data Factory
• Streaming Technologies: Kafka, Google Pub/Sub (or similar messaging systems)
• DevOps & Automation: Git, Jenkins or GitHub Actions, Azure DevOps, Terraform, Docker
• Visualization & Reporting: Power BI, Tableau, or similar BI tools
• Experience with data lake and/or data warehouse architectures (e.g., Lakehouse concepts)
• Knowledge of data governance frameworks and data quality tools
• Familiarity with CI/CD pipelines and automated data testing best practices