Data Analyst - Python, SQL & Power BI

Responsibilities: • Partner with business stakeholders to assess objectives, capture requirements, and translate them into analytics and reporting solutions. • Design, develop, and maintain dashboards, reports, and self-service datasets using tools such as Power BI, Tableau, or similar platforms. • Define and operationalize KPI definitions, calculations, and business rules; document metrics and data lineage for transparency and reuse. • Perform exploratory analysis to identify trends, patterns, anomalies, and opportunities; communicate findings through clear storytelling and data visualization. • Provide end-user support and enablement (training, documentation, office hours) to improve adoption and data literacy. • Design, build, and maintain scalable ETL/ELT pipelines (batch and/or streaming) to ingest, transform, and curate data for analytics and operational use cases. • Develop and optimize data models (dimensional models, lakehouse/warehouse schemas) to enable performant reporting and consistent analytics. • Implement data quality checks, monitoring, and automated validation to ensure accuracy, completeness, and timeliness of datasets. • Troubleshoot and resolve data issues across source systems, pipelines, and semantic/reporting layers; perform root-cause analysis and implement preventive controls. Required: • Bachelor’s degree in Computer Science, Information Systems, Engineering, Analytics, or a related field (or equivalent practical experience). • 3+ years of experience across BI/reporting and data engineering (or demonstrated ability delivering end-to-end data-to-dashboard solutions). • Strong SQL skills, including complex joins, window functions, query optimization, and working with relational databases. • Experience building dashboards and semantic models in a BI platform (e.g., Power BI, Tableau, Qlik) and translating business requirements into reporting solutions. • Hands-on experience building data pipelines using Python and/or Spark/PySpark, including data transformation and orchestration concepts. • Working knowledge of data modeling (dimensional modeling, star/snowflake schemas) and BI best practices. • Strong communication skills with the ability to explain technical topics to non-technical stakeholders.