Business System Analyst (Interoperability)

Conquest Tech Solutions Inc; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Conquest Tech Solutions Inc is seeking an experienced Healthcare Data & Business Consultant who can bridge healthcare payer domain knowledge with data engineering and analytics. The role focuses on translating Actuarial, Underwriting, and HEDIS concepts into well-defined data definitions and rules.

You will collaborate with SMEs, architects, and data engineers to document data flows, validate metrics, and support data-driven initiatives across payer operations.

Qualifications

• Strong understanding of healthcare payer operations and data.
• Experience with Actuarial, Underwriting, and HEDIS/Quality functions.
• Proficient in SQL and data analysis, with ability to profile complex datasets.
• Experience documenting data rules, mappings, and business definitions.
• Excellent communication bridging business and technical teams.

Responsibilities

• Develop understanding of payer processes, data architecture, and end-to-end data flows.
• Collaborate across payer functional areas (Actuarial, Underwriting, HEDIS/Quality).
• Document business rules, calculations, metrics, assumptions, and dependencies.
• Reverse-engineer data flows and data lineage from applications and datasets.
• Translate business concepts into data definitions, mappings, and semantic models.
• Work with architects, data engineers, analysts, and SMEs to capture knowledge into reusable documentation.
• Support analytics and AI/data-driven use cases by ensuring proper data context.

Skills

Healthcare payer domain knowledge

SQL & data analysis

Data profiling & validation

Business-rule discovery

Communication with stakeholders

Tools

Snowflake / cloud data platforms

Semantic modeling

Metadata management

Job description

Job Details

We are seeking an experienced Healthcare Data & Business Consultant with strong healthcare payer domain knowledge and hands-on data expertise. The ideal candidate will bring a solid understanding of Actuarial, Underwriting, and HEDIS/Quality functions and be able to connect these business processes to the underlying data, system architecture, and data flows.This role requires someone who can work at the intersection of healthcare business functions and data, understand how information moves across systems, identify and validate business rules and metrics, and help translate existing processes and institutional knowledge into well-defined and documented data and business definitions.The successful candidate should be comfortable working independently with business SMEs, technical teams, and data engineers to understand both what the business is trying to accomplish and how the underlying data supports those processes.

Key Responsibilities

Develop a detailed understanding of existing healthcare payer business processes, systems, data architecture, and end-to-end data flows.

Work across payer functional areas, with particular emphasis on:

• Actuarial
• Underwriting
• HEDIS / QualityClaims and healthcare cost/utilization
• Membership and enrollmentProvider data
• Premium and related financial data

Understand how data is generated, transformed, integrated, and consumed across different systems and how those data flows support key healthcare business processes.

Partner with business SMEs to understand and document existing business rules, calculations, metrics, assumptions, and dependencies.

Apply healthcare payer and actuarial knowledge to interpret and validate metrics such as:

• PMPM
• Utilization per 1,000
• Allowed and paid amounts
• Member months
• IBNR
• Medical cost and utilization trends
• Risk adjustment
• Medical Loss Ratio
• Quality/HEDIS-related measures and supporting data

Analyze and profile healthcare data to validate existing logic and identify relationships, inconsistencies, gaps, and undocumented business rules.

Reverse-engineer business logic and data flows from existing applications, datasets, queries, and processes where documentation is limited.

Translate business concepts into well-defined data definitions, mappings, semantic models, and business rules that can be understood by both technical and business stakeholders.

Partner with architects, data engineers, analysts, and healthcare SMEs to capture institutional/tribal knowledge and convert it into reusable documentation and definitions.

Support analytics and emerging AI/data-driven use cases by ensuring that the underlying healthcare data has appropriate business context, definitions, relationships, and validation.

Required Qualifications

• Strong healthcare payer domain experience, with demonstrated understanding of payer operations and data.
• Knowledge and practical exposure across Actuarial, Underwriting, and HEDIS/Quality functions.
• Strong understanding of healthcare cost and utilization concepts, including PMPM, utilization, allowed/paid amounts, member months, IBNR, trend, risk adjustment, and MLR.
• Experience working with major healthcare payer data domains, including claims, membership/enrollment, provider, premium, clinical/quality, and cost/utilization data.
• Strong ability to understand system architecture, upstream/downstream data dependencies, data lineage, and end-to-end data flows and relate them back to business processes.
• Strong SQL and data analysis skills, with the ability to independently interrogate and profile complex datasets.
• Experience with data profiling, reconciliation, validation, mapping, and business-rule discovery.
• Ability to reverse-engineer business logic from data, applications, existing queries, and conversations with SMEs.
• Experience documenting business definitions, data rules, data mappings, assumptions, and process/data flows.
• Strong analytical and problem-solving skills with the ability to operate effectively where documentation or SME availability may be limited.
• Excellent communication skills and the ability to bridge conversations between healthcare business stakeholders and technical/data teams.

Preferred Qualifications

• Experience working within a health plan or on large-scale healthcare payer transformation, analytics, or data modernization initiatives.
• Experience working with modern cloud data platforms such as Snowflake or comparable technologies.
• Exposure to semantic modeling, metadata management, business glossaries, or enterprise data models.
• Exposure to AI-enabled analytics, data agents, or natural-language-to-data solutions such as Snowflake Cortex Analyst/Agents or similar tools.
• Experience supporting initiatives requiring integration of data across multiple healthcare business functions