Senior/Principal Data Architect JD
Key Responsibilities:
- Strategic Data Leadership: Define and drive the data architecture and AI strategy in alignment with organizational goals, focusing on data-driven decision-making and improving operational efficiency.
- Architecture Design: Lead the design and implementation of scalable and efficient data architectures that support advanced analytics, reporting, and machine learning applications.
- Integration Solutions: Oversee the development of data integration strategies, enabling seamless data flow across various healthcare systems, including RCMs, EHRs, Claims, Policy Admin and Billing systems, and analytics platforms.
- Data Governance & Compliance: Establish and maintain data governance frameworks, ensuring compliance with regulations such as HIPAA, FedRAMP and HITRUST, while promoting data integrity, security, and quality.
- Collaboration with Stakeholders: Partner with executive leadership, enterprise architects, data scientists, analysts, and IT teams to understand data needs, provide architectural guidance, and ensure successful project execution.
- Emerging Technology Assessment: Evaluate and recommend emerging technologies and tools that can enhance data architecture and analytics capabilities in healthcare.
- Performance Metrics: Establish key performance indicators (KPIs) and metrics to evaluate product success and drive continuous improvement based on user feedback and data analysis.
- Documentation and Standards: Develop comprehensive documentation of data architecture standards, best practices, and processes for internal teams.
- Mentorship and Team Development: Mentor and guide data architects and data engineers, fostering a culture of continuous learning and innovation within the data team.
Experience:
- Experience: 15+ years of experience in data architecture, with a minimum of 2+ years in the healthcare domain.
- Technical Skills:
- Expertise in data engineering frameworks and tools (e.g., Apache Spark, Apache Kafka, Airflow).
- Expertise in Relational, NoSQL and Vector databases (e.g., SQL Server, Oracle Teradata, PostgreSQL, MongoDB, Cassandra, SingleStore, Pinecone).
- Proficiency in data warehousing solutions (e.g., Snowflake, Amazon Redshift, Google BigQuery, Databricks).
- Proficiency with any of the cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
- Strong experience with ETL processes and tools (e.g., Apache NiFi, Talend, Informatica, Mulesoft).
- Strong experience with Machine Learning frameworks (e.g., Python, Keras, Tensorflow).
- Strong experience with Data Visualization frameworks (e.g., Power BI, Tableau)
- Experience with Gen AI, Large Language Models, Small Language Models, RAG solutions (e.g., GPT, Llama2, Claude 2, Huggingface, Phi3, Mistral)
- Experience in Healthcare Data Interoperability frameworks (e.g., HL7 V2, HL7 V3, FHIR, SNOMED) is a plus.
- Experience with Microservices architecture, BFF, Spring, JDK, MERN or MEAN stack is a plus.
- Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.
- Regulatory Knowledge: In-depth understanding of healthcare data regulations and standards, including compliance requirements.
- Leadership Skills: Proven ability to lead cross-functional teams, and drive data initiatives from conception to execution.
- Responsible Use of AI: Familiarity with data privacy and ethical considerations in healthcare analytics.
- Analytical Mindset: Strong analytical and problem-solving skills, with a focus on delivering actionable insights from data.
- Communication Skills: Excellent verbal and written communication skills, capable of conveying complex data concepts to diverse audiences.
Qualifications:
- Engineering degree from a reputed university, Master’s degree will be a plus.
- Advanced certifications in architecture (e.g, TOGAF, AWS/Azure/GCP Solutions Architect).
- Advanced certifications in data management (e.g., CDMP, Cloud Data Architect, Cloud AI Solutions Architect, Snowflake architect).
