This is a remote position.
Work Authorization: GC, USC Only
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Strong SQL skills, including joins, aggregations, filtering, data validation, and troubleshooting.
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Hands-on experience developing Power BI reports and dashboards.
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Experience with data profiling, reconciliation, QA, and report validation.
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Familiarity with Power BI semantic models, DAX, dimensional modeling, facts, dimensions, and relationships.
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Experience documenting business requirements, reporting logic, and data validation results.
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Develop and maintain Power BI reports and dashboards using approved enterprise datasets and semantic models.
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Write SQL queries to analyze data, investigate discrepancies, validate results, and support business reporting.
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Gather and document business requirements, KPI definitions, reporting needs, and acceptance criteria.
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Create Power BI measures, visualizations, filters, and drill-through functionality.
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Validate reporting results against certified KPIs, source data, and business requirements.
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Perform data profiling, reconciliation, root-cause analysis, regression testing, and UAT support.
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Prepare test cases, source-to-target mappings, reconciliation evidence, and technical documentation.
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Identify and document data-quality issues, including duplicate records, missing identifiers, inconsistent values, and hierarchy problems.
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Support master data management initiatives, including data matching, standardization, and validation.
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Work with Data Engineering and Business Intelligence teams to validate enterprise data solutions.
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Support self-service reporting by helping business users understand approved datasets and reporting standards.
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Assist in testing AI-generated analytical responses against validated business metrics and reports.
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Maintain documentation and support continuous improvement of data validation and reporting processes.
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Bachelor's degree in Computer Science, Information Systems, Analytics, Mathematics, Finance, Business, or a related field, or equivalent practical experience.
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1 to 3 years of experience in data analysis, business intelligence, reporting, or analytics. Relevant internship or project experience may be considered.
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Working knowledge of SQL for data analysis and troubleshooting.
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Experience creating Power BI dashboards, reports, measures, filters, and drill-through functionality.
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Understanding of data modeling, semantic models, and DAX concepts.
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Experience validating business reports, reconciling data, and documenting test results.
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Ability to translate business reporting requirements into technical specifications.
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Experience working with business stakeholders, analysts, BI developers, and data engineers.
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Exposure to Azure Data Lake, Azure Data Factory, Databricks, or Microsoft Fabric.
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Experience working with Gold Layer datasets and governed enterprise data products.
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Understanding of data governance, data quality, and master data management (MDM).
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Familiarity with certified KPIs, enterprise semantic models, and dimensional data structures.
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Exposure to Databricks Genie, AI copilots, or AI-assisted analytics.
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Experience supporting enterprise data certification and self-service BI reporting.
Skills Required
- Bachelor's degree in Computer Science, Information Systems, Analytics, Mathematics, Finance, Business, a related field, or equivalent practical experience
- 1 to 3 years of experience in data analysis, business intelligence, reporting, or analytics; relevant internship or project experience may be considered
- Strong or working knowledge of SQL for data analysis, joins, aggregations, filtering, validation, and troubleshooting
- Hands-on experience creating Power BI dashboards, reports, measures, filters, visualizations, and drill-through functionality
- Understanding of Power BI semantic models, DAX, dimensional modeling, facts, dimensions, and relationships
- Experience with data profiling, reconciliation, QA, report validation, and documenting test results
- Ability to translate business reporting requirements into technical specifications
- Experience working with business stakeholders, analysts, BI developers, and data engineers
- Exposure to Azure Data Lake, Azure Data Factory, Databricks, or Microsoft Fabric
- Experience with Gold Layer datasets and governed enterprise data products
- Understanding of data governance, data quality, and master data management
- Familiarity with certified KPIs, enterprise semantic models, and dimensional data structures
- Exposure to Databricks Genie, AI copilots, or AI-assisted analytics
- Experience supporting enterprise data certification and self-service BI reporting
What We Do
Often, the biggest barrier between setting business objectives and achieving them is talent. Finding technically qualified people when you need them is hard enough. Finding technically qualified people who are the best fit for your organization is tougher. You need a staffing partner with the right expertise who can find the right talent in the right time frame, because your project can’t wait. That’s where we come in. aKube Inc is committed to leveraging its corporate values and operating model to achieve the highest level of performance and respect within the industry. We have developed a highly efficient delivery model for supporting a wide array of clients with expertise in supporting high-volume contingent worker programs.
