À propos de Mouna Priya
Anglais
Capacité professionnelle complète
Français
Capacité professionnelle limitée
Télougou
Bilingue ou natif
Expériences
- Sienna Investment Managers,Data Engineer (Intern)septembre 2025 - mars 2026 (6 mois)Paris, France• • Designed and maintained scalable ELT/ETL pipelines in Microsoft Fabric (Fabric Data Factory, Dataflows Gen2, PySpark notebooks) ingesting heterogeneous financial data from enterprise systems and APIs, reducing manual processing cycles by 40%.• • Built reusable analytical data models in Lakehouses and Warehouses, delivering business-ready datasets and efficient semantic layers for Power BI reporting and self-service analytics.• • Implemented automated data validation and quality checks across ingestion and transformation stages, improving report accuracy by 25% and ensuring data consistency and integrity.• • Monitored production data workflows, investigated data discrepancies, and resolved root causes in ingestion and transformation to keep pipelines reliable.• • Partnered with business stakeholders to translate reporting and analytical requirements into technical solutions; documented data models, business rules, and lineage for governance and maintainability.
- Infosys LimitedData Engineer / Data Analytics Engineerjuin 2022 - septembre 2024 (2 ans et 3 mois)• • Engineered and automated production-grade ETL pipelines in Python, Azure Data Factory, and Azure Databricks to ingest high-volume structured and semi-structured transactional data from multiple enterprise systems.• • Structured analytical layers on Delta Lake following Medallion Architecture (Silver/Gold), delivering clean, well-governed data assets for downstream BI and analytics.• • Optimised transformations with dbt and advanced SQL, improving query execution performance by 20% across data layers.• • Integrated Git-based CI/CD and automated deployment workflows to strengthen pipeline testing, reliability, and production stability; supported incident resolution in production environments.• • Collaborated across a global, distributed organisation with technical and business teams to turn data requirements into scalable, documented technical specifications.
- SkillDzireAI Interndécembre 2021 - juin 2022 (6 mois)• • Built an end-to-end Python data pipeline (ingestion, feature engineering, evaluation); maintained reliability and reproducibility with Git and clear technical documentation.
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Formations
- M.Sc. inEPITA2026M.Sc. in
- B.Tech inBapatla Engineering College2022B.Tech in