Data Engineer with 2 years’ experience delivering scalable solutions with PySpark, SQL, Python, and
Azure at Celebal Technologies and MX Player. Known for optimizing pipelines and collaborating across
teams to deliver in…
Data Engineer with 2 years’ experience delivering scalable solutions with PySpark, SQL, Python, and
Azure at Celebal Technologies and MX Player. Known for optimizing pipelines and collaborating across
teams to deliver insights. Eager to rejoin tech with hands-on skills and drive for impact.
Automated PySpark pipelines migrating 10+ TB data to Azure Data Lake, cutting processing time by 15%.
Developed optimized SQL data models, reducing query times by 20%.
Led 4-member team across 3 projects, boosting client satisfaction by 25%.
Delivered validated datasets to 15+ stakeholders for reporting.
Automated PySpark pipelines migrating 10+ TB data to Azure Data Lake, cutting processing time by 15%., Developed optimized SQL data models, reducing query times by 20%., Led 4-member team across 3 projects, boosting client satisfaction by 25%., Delivered validated datasets to 15+ stakeholders for reporting.
Built SQL/Python pipelines extracting social media APIs for competitor analysis, shaping product roadmaps with trend dashboards.
Created Excel/Power BI visualizations quantifying market trends, increasing stakeholder awareness by 30% via executive reports.
Designed A/B test frameworks using Python analytics, optimizing campaign performance and driving ROI improvements.
Built SQL/Python pipelines extracting social media APIs for competitor analysis, shaping product roadmaps with trend dashboards., Created Excel/Power BI visualizations quantifying market trends, increasing stakeholder awareness by 30% via executive reports., Designed A/B test frameworks using Python analytics, optimizing campaign performance and driving ROI improvements.
Streamlined data preparation using Python/PostgreSQL, improving efficiency by 20%.
Developed and optimized SQL queries to speed report generation.
Collaborated to ensure data quality and support insights.
Streamlined data preparation using Python/PostgreSQL, improving efficiency by 20%., Developed and optimized SQL queries to speed report generation., Collaborated to ensure data quality and support insights.
Developed deep learning chatbot using neural networks/bag-of-words, achieving 85% accuracy., Automated workflows for 100+ queries daily, boosting accuracy/efficiency., Built scalable NLP models improving chatbot performance.
Developed deep learning chatbot using neural networks/bag-of-words, achieving 85% accuracy.
Automated workflows for 100+ queries daily, boosting accuracy/efficiency.
Built scalable NLP models improving chatbot performance.
• Engineered end-to-end scalable data pipelines using Azure Data Factory for orchestration, ingesting and transforming multi-source data into AWS Redshift and Azure Blob Storage. Designed real-time workflows, batch ETL, data cleansing, validation, and optimized SQL models, reducing processing time by 30% and enabling efficient analytics and BI reporting.
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