Architect Rr/1190/2024

**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.
- **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).