Data Engineer With 6 years of experience in automating infrastructure management, designing efficient ETL workflows, and leading successful project deliveries. Proficient in Building and maintaining data pipelines using …
Data Engineer With 6 years of experience in automating infrastructure management, designing efficient ETL workflows, and leading successful project deliveries. Proficient in Building and maintaining data pipelines using cloud services like AWS, GCP, and Azure, Skilled in implementing scalable data warehouses using technologies such as Snowflake, Redshift, BigQuery, and Big Data Tools Hadoop, Kafka, and Azure HDinsight, with strong background in data streaming, SQL, and data visualization tools like Power BI and Tableau.
Automated infrastructure management with Terraform, reducing deployment time by 51% in AWS Environment
• Designed AWS Data Pipeline workflows for efficient ETL, which reduced data processing time by 42%.
• Utilized Tools S3, EC2, RDS, Redshift, EMR, Snowflake, dbt, ETL, MapReduce, EMR, Glue, SQL, Lambda.
• Analyzed data using Power BI to identify anomalies and limit discrepancies by 26%.
• Led a team of 1 full-time employee and 3 contractors and collaborated with Data Scientists and Data Analysts.
• Implemented scalable Snowflake data warehouses, boosting data transformation efficiency by 30% with dbt.
Automated infrastructure management with Terraform, reducing deployment time by 51% in AWS Environment
Designed AWS Data Pipeline workflows for efficient ETL, which reduced data processing time by 42%
Utilized Tools S3, EC2, RDS, Redshift, EMR, Snowflake, dbt, ETL, MapReduce, EMR, Glue, SQL, Lambda
Analyzed data using Power BI to identify anomalies and limit discrepancies by 26%
Led a team of 1 full-time employee and 3 contractors and collaborated with Data Scientists and Data Analysts
Implemented scalable Snowflake data warehouses, boosting data transformation efficiency by 30% with dbt
Developed and Maintained data pipelines using Azure Services resulting 40% increase in data processing speed
Created data transfer pipelines from On-prem system to Azure services, increasing 95% network throughput
Deployed Apache Spark on Azure VMs for 40% more efficient data processing
Automated operations with PowerShell and Azure cloud shell, Increased 30% productivity
Use ADF for ETL workflows, enhancing data processing efficiency and SQL data warehouse optimizations by 50%
Built and deployed big data solutions using Hadoop and Azure HDInsight, improving data processing efficiency by 30%
Reduced migration costs of large data sets across multiple cloud providers by 50%
Use C++ to develop high-performance data processing applications and systems
Used Azure-based streaming services, Azure Kafka, Azure Event Hubs, Azure Stream Analytics, and Azure Databricks
Proficient in Data Streaming, Elasticsearch, Flink, Hadoop, Java, Kafka, MongoDB, SQL, Spark, and Tableau
Created SQL code to extract and transform data for business requirements, increasing accuracy by 95%
Enhanced data processing efficiency by 30% and reduced deployment time by 20%
Automated data pipeline for build, test, release, and deployment using Jenkins
Developed Tableau visuals and dashboards to provide insights into key performance trends
Implemented ETL process to streamline data import from various sources into GCP BigQuery warehouse
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