Senior Data Architect

2 weeks ago

bangalore, India Emids Full time
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).

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