Data Engineer for Healthcare

Job Description

Sand Technologies is seeking a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure to support data-intensive applications and analytics solutions. The Data Engineer will work closely with cross-functional teams to contribute to the strategic direction of the company's data initiatives.

Responsibilities:

• Lead the design, implement, and maintain scalable data pipelines.
• Architect scalable and efficient data solutions using appropriate architecture design.
• Design and optimize data models and schemas.
• Develop, optimize, and automate ETL workflows.
• Utilize big data technologies such as Spark, Kafka, and Flink.
• Deploy and manage data solutions on cloud platforms such as AWS, Azure, or GCP
• Implement and oversee data governance, quality, and security measures.
• Monitor data pipelines and infrastructure performance.
• Build and maintain basic CI/CD pipelines.
• Collaborate with cross-functional teams.
• Create and maintain technical documentation.
• Mentor and guide junior and mid-level data engineers.
• Evaluate and recommend technologies, frameworks, and tools.
• Optimize software performance, scalability, and efficiency.

Requirements:

• Proven experience as a Data Engineer, or in a similar role.
• Proven experience working with Big Data and tools used to process Big Data
• Strong problem-solving and analytical skills.
• Excellent understanding of data engineering principles and practices.
• Excellent communication and collaboration skills.
• Ability to adapt to new technologies.
• Ability to write clean, scalable, robust code using python or similar programming languages.
• Knowledge of data governance frameworks and practices.
• Understanding of machine learning workflows.

The role offers:

• Opportunity to work with cutting-edge cloud-based data projects.
• Exposure to a variety of data architectures.
• Chance to work across a variety of data architectures such as Data Mesh, lakehouse, data vault and data warehouses.
• Be part of a fast-growing enterprise AI company.