Data Analytics Business Analyst (Full-Time Remote, North Carolina)

The Data Analytics Business Analyst gathers and documents business and technical needs for data and analytics projects, converts them into analytical specifications and test plans, assists in building and validating dashboards, reports, and predictive models, and safeguards data quality and HIPAA compliance across all analytical solutions.

Elicit and Document Analytics Requirements

• →Lead discovery meetings to capture business objectives, key performance indicators (KPIs), and reporting needs
• →Capture data source requirements, frequency, granularity, and any service level expectations (e.g., refresh windows)
• →Produce requirements artifacts such as Business Requirements Documents (BRDs), data modeling diagrams, and acceptance criteria that define the desired analytics outcomes
• →Analyze and Profile Data Perform data profiling on source systems (e.g., relational databases, data lakes, SaaS APIs) to understand completeness, consistency, and distribution of fields
• →Conduct gap analysis to identify missing attributes or mismatches against reporting specifications
• →Document data quality issues, propose validation rules, and define reconciliation procedures that support accurate analytics

Translate Requirements into Analytical Specifications

• →Develop detailed functional and technical specifications for data models, dimensional schemas (star/snowflake), and analytical pipelines (ETL/ELT, data wrangling scripts, BI tool configurations)
• →Collaborate with data engineers, data scientists, and BI developers to align design patterns, naming conventions, and reusable components
• →Ensure specifications address scalability, security (including HIPAA related data handling), and maintainability of analytical solutions

Plan and Execute Testing of Analytical Solutions

• →Create test plans, test cases, and validation data sets for unit, integration, and user acceptance testing of dashboards, reports, and predictive models
• →Support business stakeholders with UAT; log defects, prioritize fixes, and oversee retesting cycles
• →Verify performance (e.g., query response time, model runtime) against agreed upon thresholds

Support Implementation and Ongoing Operations

• →Assist with go live activities such as preparation of runbooks, standard operating procedures (SOPs), and cut over checklists for analytics releases
• →Monitor initial production runs, perform data reconciliations, and address any discrepancies that arise
• →Participate in incident response, root cause analysis, and documentation of lessons learned for continuous improvement

Maintain Documentation and Knowledge Base

• →Keep current inventories of data sources, data dictionaries, lineage diagrams, and model documentation up to date
• →Author and refresh end user guides, technical “how to” documents, and metadata catalogs in line with departmental standards

Communication and Collaboration

• →Translate complex analytical concepts into clear language for both technical and non technical audiences
• →Partner with internal business units, external data providers, and vendor teams to ensure alignment on data definitions, delivery schedules, and reporting expectations
• →Contribute to data governance initiatives, supporting standards for data stewardship, privacy, and compliance

Continuous Improvement

• →Identify opportunities to streamline analytics workflows through reusable templates, automation (e.g., CI/CD pipelines for data models), and self service tooling
• →Define and track analytics related KPIs such as report delivery timeliness, data quality error rates, and model accuracy
• →Recommend best practice enhancements to increase efficiency, data reliability, and user satisfaction

Education and Experience

Vocational or Technical Training in in Computer Science, Information Systems, Business Administration, or a related field; and six (6) years of experience in data analytics or data science;

Or

Associate’s degree from an accredited university in Computer Science, Information Systems, Business Administration, or a related field; and five (5) years of experience in data analytics or data science;

Or

Bachelor’s degree from an accredited university in Computer Science, Information Systems, Business Administration, or a related field; and five (3) years of experience in data analytics or data science.

• SQL (preferably T-SQL)
• Communication skills
• Data Visualization Tools
• Software Development Life Cycle (SDLC)
• Data Governance
• Documentation Tools and Platforms

$81,873-104,388/Annually