Health Care Data Architect / Lead

Duties and responsibilities
• Lead the activities related to the Conceptualization, Design, Development and Evaluation of
Healthcare big data analytics solutions
• Leads and coordinate the technical and business discussions relative to future solution direction
• Able to lead meetings with customer teams / Sr. Mgmt. to gain approval on recommendations and
implementation plan
• Collaborate in defining solution architecture for Master Data Management (MDM) & help set
information architecture standards and methodologies
• Define and implement data quality processes and analytical production performance indicators and
• Monitor Industry & Technological trends in Healthcare Analytics Space and support the evolution of
the platform and solution offerings that can be positioned with customers
• Device Strategies to quickly develop solution / re-usable components to meet customer needs
• Own Project Scoping, Planning, Estimation and Participate in Team setup & Work allocation for
successfully delivering the Program / Solution
• Responsible for design reviews & build consensus on areas for improvement.
• Responsible for communication of Program charter, milestones etc.
Key Skills
• Bachelor’s/Master’s degree is preferred in computer science or related field (such as computer
engineering, software engineering, biomedical engineering, or mathematical sciences)
• ~ 5 - 7 years of industry experience in building Data Analytics solutions preferably in healthcare
• Strong verbal / communication, written & presentation skills
• Required Competencies in Leading, Mentoring teams in Developing Healthcare Analytical solutions
• Experience in Agile Software Development, programming and coding
• Preferred Technical Competencies: Expertise in development of Big data Analytics Solution using
- Distributed computing, Hadoop cluster management, HDFS, MapReduce
- Stream-processing solutions such as Storm or Spark
- Data querying tools such as Pig, Impala and Hive, data integration
- SQL & NoSQL Databases such as MongoDB, Cassandra, and HBase
- Big data toolkits such as H2O, SparkML, and Mahout and Messaging systems such as Kafka and
- Proficient in Programming with R, Python, Ruby, C++, Perl, Java, SAS, SPSS.
- Exposure & familiarity with ETL tools, data APIs, data modeling, Algorithms and data warehousing
- Exposure to Healthcare systems and data exchange mechanisms

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