Build and maintain Streamlit dashboards for business reporting and operational insights.
Optimize dashboard performance (query tuning, caching strategies, efficient data loading, and rendering).
Design, develop, and maintain SQL tables, views, and models that feed dashboards.
Implement and maintain Python-based data workflows to transform, validate, and deliver data for analytics use cases.
Monitor and improve data quality, freshness, and completeness (including automated checks and alerting).
Partner with stakeholders to define metrics, ensure consistent definitions, and translate requirements into data products.
Maintain documentation for dashboards, datasets, KPI definitions, and data lineage.
Troubleshoot data and dashboard issues, providing timely support and root-cause analysis.

Strong experience with SQL (complex joins, window functions, performance optimization, and data modeling).
Strong experience with Python for data work (e.g., pandas, data validation patterns, and APIs as needed).
Experience building dashboards using tools such as Streamlit (ideal), Looker, Tableau, etc.
Solid understanding of analytics engineering fundamentals: dimensional modeling, metric definitions, and reproducible transformations.
Knowledge of basic software engineering practices (Git workflows, code reviews, testing, CI/CD)

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