Data Engineer
Summary
A data engineer at a medical diagnostics company who designs, builds, and maintains scalable data pipelines and ETL processes to support analytics and business intelligence, working with SQL, Python, cloud platforms (AWS/Azure/GCP), and optionally big data tools like Spark, Hadoop, or Kafka.
Job Description:
Design, develop, and maintain scalable data pipelines and architectures to support analytics and business intelligence initiatives.
Integrate data from multiple sources, ensuring consistency, reliability, and data quality.
Collaborate with data analysts, scientists, and other stakeholders to define data requirements and optimize data workflows.
Implement ETL (Extract, Transform, Load) processes for structured and unstructured data.
Monitor and troubleshoot data systems to ensure performance, security, and efficiency.
Document data processes, system configurations, and best practices.
Requirements:
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
Proven experience with SQL, Python, and data pipeline frameworks.
Strong understanding of data warehousing concepts and cloud platforms (e.g., AWS, Azure, or Google Cloud).
Experience with big data technologies such as Spark, Hadoop, or Kafka is an advantage.
Excellent problem-solving, analytical, and communication skills.
Ability to work both independently and collaboratively in a fast-paced environment.
Benefits:
Competitive salary and performance-based incentives.
Opportunities for professional development and technical training.
Innovative and collaborative work culture.
Flexible or hybrid working arrangements.