Big Data Architect - Healthcare

Job Summary

The Big Data Architect will be responsible for designing, implementing, and managing large-scale data systems, ensuring they are scalable, secure, and aligned with business objectives. The role involves working with a variety of data technologies, cloud platforms, and legacy systems to create integrated solutions that support advanced analytics, business intelligence, and data governance. This position requires a highly skilled professional with extensive experience in data architecture, cloud technologies, and ensuring compliance with regulatory standards.

Qualifications

• Education:
  • Bachelor's degree in Computer Science, Data Science, Information Systems, or a related discipline is required.
  • Master's degree in a similar field is preferred.
• Certifications:
  • Relevant certifications such as TOGAF, AWS Certified Solutions Architect, Google Professional Data Engineer, or equivalent are strongly recommended.

Experience

• At least 8 years of experience in data architecture, with a proven track record of designing scalable, high-performance data systems for big data environments.
• Hands-on experience in integrating legacy systems with cloud platforms (e.g., AWS, Google Cloud, Azure, Cloudera, Databricks) and modern big data technologies (e.g., Hadoop, Spark, Kafka).
• Healthcare Data Management: Knowledge of healthcare data types, data governance, and regulatory compliance (e.g., HIPAA, GDPR).
• Experience working with large-scale data storage solutions and distributed computing technologies (e.g., NoSQL databases, Hadoop, Spark).
• Hands-on experience with Cloudera Databricks and other big data platforms.
• Familiarity with the complexities of working with healthcare-specific data, including patient records, medical imaging, claims, and other clinical data types.

Skills

• Big Data Expertise: Advanced knowledge of big data technologies and architecture, including Hadoop, Spark, Kafka, and NoSQL databases (e.g., Cassandra, MongoDB).
• Cloud Platforms: Expertise in working with cloud platforms such as AWS, Google Cloud, and Microsoft Azure, including experience with cloud-based big data services (e.g., AWS Redshift, Google BigQuery).
• Data Security & Privacy: Strong understanding of data security practices, including encryption, access control, and compliance with data protection regulations.
• Leadership & Collaboration: Strong leadership skills with the ability to collaborate effectively with cross-functional teams, including data scientists, engineers, and business stakeholders.
• Problem-Solving: Excellent analytical and problem-solving skills, with the ability to design complex data systems that meet business and technical requirements.
• Communication: Strong communication skills, both written and verbal, with the ability to present complex technical concepts to non-technical stakeholders.