About Bhuwanesh
English
Native or bilingual
Experience
- Saksoft,Data Scientist"July 2025 - March 2026 (8 months)• • Experience with AWS Bedrock for foundation model access, prompt orchestration, and inference optimization• • Hands-on with AWS Agent frameworks (AgentCore / Bedrock Agents) for building autonomous task execution systems• • Designed multi-agent systems using orchestration frameworks (LangChain / LangGraph / Strands SDK)• • Optimized Athena query performance and table layouts through partitioning strategies and file optimization.• • Developed modular and reusable code components following engineering best practices.• • Led end-to-end data science delivery as an individual contributor, owning problem formulation, modelling approach, and client-facing insights.• • Writing Python, Pyspark & SQL queries to extract, transform and load data on Azure & GCP.• • Implemented Spark performance optimizations including partitioning, bucketing, broadcast joins, caching, and adaptive query execution to reduce job runtimes and infrastructure costs.• • Built end-to-end data pipelines integrating Azure Databricks with Azure Data Lake Storage (ADLS Gen2), Azure Blob Storage, Azure SQL etc.• • Built advanced Power BI reports and dashboards using optimized data models, complex DAX, and Azure-integrated data sources to support enterprise analytics and reporting.
- Grethena,"Senior Data Engineer"August 2024 - May 2025 (9 months)• • Addressed data inconsistencies, bias, and redundancy through rigorous preprocessing, sampling strategies, and validation.• • Followed Azure Databricks development standards to modularize transformations, validate schema changes, and manage dependencies using notebooks and jobs.• • Designed and developed advanced Power BI dashboards and reports for executive and operational analytics, enabling data-driven decision making across business teams.• • Integrated Power BI with Azure Databricks, ADLS, Azure SQL, and BigQuery using Import, DirectQuery, and composite models based on performance requirements.• • Building efficient data pipelines using Cloud Data Fusion and different social channels (Facebook, Instagram channels, App data etc.) as source and GCS/BigQuery as Sink.• • Designed RAG pipelines with embeddings and vector databases for enterprise knowledge retrieval• • Implemented multi-agent orchestration patterns using LangChain / Strands SDK• • Designed and developed high-throughput data processing pipelines handling large-scale datasets• • Built REST APIs for exposing processed data and ML predictions to downstream systems• • Collaborated with cross-functional teams to understand data requirements and provide effective solutions.
- Blue Yonder,"Senior Data Scientist"May 2024 - August 2024 (3 months)• • Built ML models for forecasting and optimization; automated pipelines using Airflow + MLflow.• • Developed dashboards and insights using SQL + Python-based data analysis.• • Created ADF pipelines for ingestion and transformation into centralized data warehouse.• • Engage with Stakeholders to gather comprehensive project requirements and demonstrated strong communication skills in translating needs into actionable plans.• • Perform data analysis and finding RCA of data related issues using Python and SQL.
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Education
- Azure Data Science Associate (DP100)Azure Data Science Associate (DP100)
- Databricks Certified Data Engineer AssociateNTT Data AcademyDatabricks Certified Data Engineer Associate