Binaya Khadka Email & Phone Number

Chicago, Illinois, United States

• Designed and implemented scalable data pipelines using Python and SQL, improving data processing efficiency by 25%.• Developed and maintained ETL processes for data warehousing solutions using tools like Apache NiFi and Informatica.• Implemented data validation and monitoring solutions, reducing data discrepancies and ensuring data integrity.• Migrated on-premises databases to cloud platforms such as AWS and Azure, enhancing data accessibility and scalability while reducing operational costs by 15%.• Extensively utilized AWS services including EC2 for virtual server management, S3 for scalable storage solutions, and Redshift for data warehousing and analytics, ensuring efficient and scalable data engineering processes.• Collaborated with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights.• Conducted performance tuning of SQL queries and database systems, achieving a 30% reduction in query execution time.• Created Python-based scripts for efficient data ingestion into AWS RDS and S3, ensuring seamless data flow and integrity.• Enhanced data integrity and data access by using SQL queries on different platforms like Snowflake, redshift, PostgreSQL, and MySQL.• Played a pivotal role in the development and maintenance of CI/CD pipelines using Jenkins, enhancing code deployment efficiency and ensuring seamless integration with GitHub for version control.• Innovated real-time data ingestion solutions by integrating Kafka with Spark Structured Streaming, enabling the capture and processing of streaming data for immediate insights.• Ensured data governance and compliance by implementing metadata management practices in Databricks, documenting data lineage, quality rules, and audit trails.• Enhanced data-driven decision-making by applying machine learning techniques with TensorFlow, resulting in a 20% improvement in predictive analytics accuracy.

Charlotte, North Carolina, United States

• Designed and implemented robust data architecture solutions, enabling efficient data storage, retrieval, and analysis.• Leveraged big data technologies such as Hadoop, Spark, and Kafka to process and analyze large datasets, enhancing data processing capabilities by 40%.• Developed real-time data processing solutions using Apache Kafka, Spark Streaming, and PySpark, enabling instant data insights, resulting in improvement in customer experience through real-time analytics.• Integrated diverse data sources, including relational databases, NoSQL databases, and third-party APIs, into a unified data platform.• Automated data workflows and ETL processes using Apache Airflow, reducing manual intervention and improving process reliability.• Ensured data security and compliance with industry standards and regulations, implementing encryption, access controls, and data masking techniques.• Leveraged advanced data storage techniques in Snowflake, such as columnar storage and optimized indexing, to achieve cost-effective storage solutions and swift data retrieval.• Created and maintained dynamic BI dashboards and reports using Tableau, Power BI, and Looker, enabling real-time data visualization and informed decision-making.• Conducted thorough data profiling and cleansing using tools like AWS Data Wrangler and Talend, ensuring data integrity and establishing robust data governance frameworks, laying the groundwork for trusted data analysis and insights.• Implemented comprehensive data quality checks, anomaly detection, and validation protocols, guaranteeing the accuracy and reliability of data across platforms like Snowflake and Databricks.• Acted as a liaison across teams, guiding complex data projects aligned with business goals. Fostered agility and innovation, significantly boosting project success and efficiency by enabling cross-functional collaboration and strategic leadership.

Richmond, Virginia, United States

• Conducted detailed data analysis using SQL, Excel, and Python, uncovering key insights and trends that informed business strategy and operations.• Developed and maintained interactive dashboards and reports using tools like Tableau and Power BI, providing stakeholders with real-time access to critical data.• Applied statistical techniques and machine learning models to analyze customer behavior, credit risk, and marketing effectiveness, contributing to a 20% increase in customer acquisition.• Cleaned and transformed raw data into actionable datasets, ensuring data accuracy and consistency for reliable analysis and reporting.• Worked closely with Data Engineers to enhance ETL processes, providing data quality feedback to refine pipelines for robust data handling.• Supported machine learning initiatives by preparing and refining datasets for Data Scientists, aiding in model development and improvement.• Utilized Kafka and Spark Streaming for real-time data insights, extracting valuable information from dynamic data sources.• Ensured data security and compliance with access controls and regulations, maintaining data integrity and aligning with privacy standards.• Drove innovation by exploring new analysis techniques and staying updated with emerging trends and technologies in data analysis.• Documented processes, models, and analyses to create comprehensive records, enhancing transparency and future decision-making• Worked closely with cross-functional teams, including marketing, finance, and IT, to understand data needs and deliver tailored analytical solutions.• Identified and implemented process improvements to enhance data quality and streamline reporting workflows, reducing report generation time by 30%.