Job description
Role Descriptions: This role is part of our engineering organization and is responsible for translating business requirements into clear, actionable technical specifications. The integration Analyst serves as a liaison between business and technical teams, helping to simplify complex business needs into well-defined technical requirements.
As an Integration Analyst, you will be part of a Scrum team, working closely with product managers, developers, and other technology and business stakeholders. You will leverage your analytical and technical expertise to drive effective solutions.
A key responsibility of the role is to create and maintain integration mapping documentation, including HL7 and other data formats, defining accurate mappings between source and destination systems.
Gather and analyze requirements for integrations between internal applications and external partner systems.
Interpret and work with HL7 (v2.x, v3), FHIR, XML and other data/message structures.
Create and maintain source-to-target data mapping documentation.
Analyze source and target system data structures to identify gaps, inconsistencies, and data quality issues
Define transformation logic, field mappings and data rules.
Collaborate with technical teams implementing the interfaces and transformations .
Collaborate with the product manager, business and development teams to define user stories, acceptance criteria, and sprint goals.
Participate in daily stand-ups, sprint reviews, and retrospectives to share progress, discuss challenges, and identify opportunities for optimization.
Collaborate with QA analysts to validate data integrity and troubleshoot any issues related to tracking implementation or data discrepancies.
Act as a subject matter expert in Quest HL7 standards and integration best practices.
Required skills:
5 years of experience as an integration analyst, healthcare data analyst or similar role
3 years of hands-on experience working with HL7 (v2.x, v3) message structures and standards (ADT, ORU, ORM etc)
Hands-on experience with data mapping and transformations rules
Strong understanding of healthcare workflows (especially patient registration, orders, results, billing workflows and message formats)
Experience working with data formats such as HL7, XML, JSON, FHIR etc
2 years of experience working in Agile/Scrum environment
Experience with Jira for managing stories and backlog
Experience writing user stories and acceptance criteria
Ability to closely work with businesses, product managers and developers to prioritize backlog items
Ability to manage multiple priorities in a fast-paced environment.
Physical and Mental Requirements:
Proven ability to sift through data, identify critical information, analyze, and make recommendations that influence successful product outcomes
Self-driven, highly motivated individual
Bachelor's degree in Science, Business, Computer Science, or a related field
Keyword:
Skills: Java XML Technologies (XML| XSL| FO| JAXP| JAXB)
Experience Required: 10 & Above
Most Popular Data Analyst Job Categories
Data Mining
Entry Level Data Analyst Sql Tableau
Home Based Data Analyst
No Experience Data Analytics
Full Time Data Analyst
Performance And Data Analyst
Part Time Excel Vba
Senior Data Analyst Ibm
Full Time Data Analyst Sql Excel
Senior Exempt Data Analyst
Other Helpful Pages Related To Data Analyst
Entry Level Tableau Developer Salaries
Entry Level Tableau Developer Career Research
Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Analyst?
A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.
Q: What is the career path for a Data Analyst?
A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.
