Birendra Chhetri Email & Phone Number

United States

United States

San Francisco, California, Us

 Leveraged Apache Spark and AWS Glue to redesign data pipelines, achieving a 40% boost in efficiency, directly contributing to a $500k annual savings by streamlining ETL processes. Integrated TensorFlow and PyTorch models into our data architecture, improving predictive analytics capabilities, which led to a 15% increase in customer retention rates. Deployed a real-time data streaming architecture using Apache Kafka and Amazon Kinesis, enabling instant data processing and ingestion, crucial for timely decision-making in our dynamic market environment. Implemented cloud-native data warehousing with Snowflake and Amazon Redshift, cutting storage costs by 20% while boosting query performance, demonstrating effective cost management and technical proficiency. Adopted Docker and Kubernetes for containerization and orchestration, reducing deployment times by 70% and improving system scalability. Integrated AWS IAM and Azure Active Directory, enhancing data security and compliance, pivotal in maintaining trust and safeguarding sensitive information. Utilized Azure Databricks to foster a collaborative environment for data analytics and machine learning, leading to a 30% reduction in project delivery times. Processed 1 million data records per second in real-time, setting a new benchmark for data throughput and efficiency in our operations. Led workshops on Big Data tools and cloud services for cross-functional teams, enhancing team skills and fostering a culture of continuous improvement and innovation.Environment and Technologies: Apache Spark, PySpark, AWS Glue, TensorFlow, PyTorch, Apache Kafka, Amazon Kinesis, Snowflake, Amazon Redshift, Docker, Kubernetes, AWS IAM, Azure Active Directory, Azure Databricks, Hadoop ecosystem, Hive, SSIS, Jenkins, GitLab CI, Azure DevOps.

Bellevue, Wa, Us

 Developed and maintained scalable data pipelines using Google Cloud services, enhancing telecom data integration and network optimization by 30%, leading to improved customer service quality. Created comprehensive big data solutions with Hadoop and Apache Spark, processing vast data volumes in real time, which enabled predictive modeling for network enhancements. Utilized machine learning for log clustering in Splunk, improving operational insights and contributing to a 10% reduction in network failures. Optimized Kafka and AWS Lambda for efficient data ingestion from massive log volumes, reducing processing latency by 15% and enhancing system responsiveness.Environment and Technologies: Google Cloud services (BigQuery, Dataflow, Storage, Cloud Functions, Cloud Run), Apache Spark, Hadoop, Splunk, Kafka, Hive, Pig, SQL, AWS, Azure, GCP, Spark Streaming, Kafka Streams, Snowflake, Redshift, Python.

Minnetonka, Mn, Us

 Directed data collection and analysis using SQL, SAS, and Python, revealing critical healthcare trends and contributing to a 40% improvement in KPI monitoring for patient care outcomes. Developed predictive models to forecast healthcare trends, significantly optimizing resource allocation and positively impacting patient care services. Established rigorous data cleansing and validation processes, ensuring high data accuracy for analysis and compliance with healthcare regulations, like HIPAA. Produced interactive dashboards and reports in Tableau and Power BI, providing stakeholders with actionable insights and supporting a data- informed decision-making culture.Environment and Technologies: SQL, SAS, Python, Pandas, NumPy, Scikit-learn, Apache Spark, Hadoop, Tableau, Power BI, HIPAA compliance.