Senior Data Engineer
P
PearsonEducation technology
Source API remote eligibility restrictions: United StatesFull-TimeSenior
SalaryThe full-time salary range for this position is between $100,000 - $110,000. This position is eligible to participate in an annual incentive program
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Job Details
- Experience
- 4+ Years of practical experience with Power BI; 3–5 years of experience in Power BI development, business intelligence, data analysis, or a related area
- Required Skills
- SQLMicrosoft Power BI
Requirements
- Have 4+ years of practical Power BI experience, including report development, visualizations, DAX, Power Query, and semantic modeling.
- Know data modeling concepts, including star schema and fact/dimension design.
- Have experience with SQL and structured datasets in data warehouses or lakehouses.
- Be familiar with data pipelines and integration concepts, such as Azure Data Factory and ETL/ELT patterns.
- Have independently delivered reporting solutions from requirements through deployment and support.
- Have experience building or supporting reports and dashboards for operational or business decision-making.
- Be able to troubleshoot data, performance, and visualization issues.
- Have experience improving data quality, reliability, and usability.
- Work cross-functionally with engineering, analytics, and business teams.
- Maintain strong documentation and knowledge-sharing practices.
- Experience with Tabular Editor 3, DAX Studio, or ALM Toolkit is helpful.
- Preferred experience includes education, EdTech, multi-tenant data environments, Google BigQuery, data governance, lineage, semantic layer standardization, or self-service analytics at scale.
Responsibilities
- Design and develop Power BI dashboards and reports for school operations, student outcomes analysis, and enterprise reporting.
- Translate business needs into visualizations aligned with reporting standards.
- Build and maintain governed, reusable Power BI semantic models.
- Apply star schema, DAX optimization, and row-level security practices.
- Validate data outputs and consistency between reports and source systems.
- Troubleshoot data discrepancies, refresh failures, and performance issues.
- Contribute to monitoring, testing, and documentation of reporting solutions.
- Work with stakeholders to refine requirements and prioritize features.
- Support self-service analytics with documented datasets and consistent definitions.
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