Test Data Analyst at Softeta handling data validation and analysis to support banking solutions. Collaborating with teams to maintain data integrity and deliver quality testing strategies.
About the role
- Data Analytics Business Analyst responsible for gathering and documenting business needs for analytics projects. Collaborating with data engineers and scientists to create validated dashboards and reports.
Responsibilities
- Gather and document business and technical needs for data and analytics projects
- Convert needs into analytical specifications and test plans
- Assist in building and validating dashboards, reports, and predictive models
- Safeguard 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
- 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
- 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
Requirements
- Vocational or Technical Training 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
Benefits
- Medical
- Dental
- Vision
- Life
- Long and Short-Term Disability
- Generous retirement savings plan
- Flexible work schedules including hybrid/remote options
- Paid time off including vacation, sick leave, holiday, management leave
- Dress flexibility
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