Principal: Data Architect

Job Title Principal Data Architect Experience 15 years 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 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 - 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 such as Apache Spark Apache Kafka and Airflow - Proficiency in relational NoSQL and vector databases including SQL Server Oracle Teradata PostgreSQL MongoDB Cassandra SingleStore and Pinecone - Proficiency in data warehousing solutions like Snowflake Amazon Redshift Google BigQuery and Databricks - Experience with cloud platforms such as AWS Azure or Google Cloud and their data services - Strong experience with ETL processes and tools such as Apache NiFi Talend Informatica and Mulesoft - Experience with machine learning frameworks like Python Keras and TensorFlow - Expertise in data visualization tools such as Power BI and Tableau - Experience with generative AI large and small language models and retrieval-augmented generation RAG solutions such as GPT Llama2 Claude 2 and Huggingface - Familiarity with healthcare data interoperability frameworks including HL7 V2 HL7 V3 FHIR and SNOMED is a plus - Experience with microservices architecture BFF Spring JDK MERN or MEAN stack is a plus - Familiarity with big data technologies such as Hadoop and 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 a Master s degree is a plus - Advanced certifications in architecture such as TOGAF or AWS Azure GCP Solutions Architect - Advanced certifications in data management including CDMP Cloud Data Architect Cloud AI Solutions Architect or Snowflake Architect