Senior Associate, Business Intelligence Engineering
J
JobgetherBusiness Intelligence
Based in the United StatesFull-TimeSenior
Salary90,000 - 115,000 USD per year
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Job Details
- Experience
- At least 3 years
- Required Skills
- PythonSQLMicrosoft Power BIData modelingDatabricksPySpark
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or an equivalent combination of education and experience.
- At least 3 years of hands-on experience developing production BI and analytics solutions with significant ownership of Power BI semantic models and data modeling.
- Advanced proficiency in Power BI, DAX, and Power Query (M), including context transition, time intelligence, and performance tuning.
- Strong dimensional modeling expertise, including star schemas, conformed dimensions, and slowly changing dimensions.
- Advanced SQL capabilities, including window functions, common table expressions, and complex joins.
- Working proficiency in PySpark or Python for transformation, automation, and pipeline development.
- Experience with modern cloud data platforms like Databricks, Delta Lake, and Unity Catalog.
- Experience building and troubleshooting orchestrated data pipelines using Databricks Workflows or Azure Data Factory.
- Ability to translate business requirements and mockups into scalable technical solutions.
- Strong independent judgment, communication, and problem-solving skills.
Responsibilities
- Own the end-to-end technical delivery of production Power BI reports and dashboards, ensuring usability, performance, accessibility, governance, and long-term maintainability.
- Design, maintain, and govern Power BI semantic models, including star schemas, reusable DAX measures, calculation groups, and row-level security.
- Partner with Product Management to validate technical feasibility, identify data gaps, clarify requirements, and estimate effort.
- Develop and maintain reliable data ingestion and transformation pipelines using Spark SQL, PySpark, Delta Live Tables, and Databricks Workflows.
- Investigate and resolve data quality, reconciliation, integrity, and performance issues at the appropriate source layer.
- Optimize Power BI reports, semantic models, and data pipelines through query tuning, aggregation strategies, and model optimization.
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