Yamir A.
Data Engineer

Skills

Transact-sql

Spark

Scala

Apache Hadoop

Neo4j

Java

Python

Mongodb

Microsoft Azure

Amazon Aws

Google Cloud

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Bio

Senior Data Engineering Consultant and Data Architect, with expertise in Data Lake solutions, Lambda Architecture, and Fast Data across cloud platforms such as AWS, Google Cloud, and Microsoft Azure. Holds a Master's degree in Big Data and possesses extensive experience in areas including Business Intelligence, Data Warehousing, NoSQL databases, analytics, machine learning, and graph solutions.

Data Architect | Big Data Specialist
8/2/2019 - 2/2/2020

Developed advanced expertise in managing and utilizing Amazon S3 for storage and data retrieval, while efficiently handling data formats with Parquet. Gained comprehensive experience in using Amazon Athena for querying data in S3 with SQL. Demonstrated capabilities in data warehousing using Amazon Redshift and leveraging Redshift Spectrum for querying data across the data lake.

Excelled in big data processing with Apache Spark, utilizing Scala and Python for developing and deploying data processing applications. Proficient in orchestrating serverless computing tasks using AWS Lambda and AWS Glue for ETL operations. Skilled in managing big data workloads using AWS EMR.

Expanded knowledge in full-text search and analytics through Elasticsearch. Streamlined data movement and transformations using Streamsets. Mastered containerization with Docker and orchestrated containerized applications with Kubernetes.

Proven proficiency in message queuing services using AWS SQS and expertly handled both NoSQL and relational databases, including DynamoDB, Oracle, and Cassandra.
Sr. Big Data Engineer
8/2/2018 - 7/2/2019

Developed expertise in Hadoop, Hive, and Spark, leveraging these technologies for efficient big data processing and analysis tasks. Skilled in managing and maintaining Linux-based systems. Proficient in Scala and Java, used for developing complex applications and data processing pipelines. Demonstrated capability in using Impala for real-time SQL querying on large datasets. Accumulated extensive experience with Accumulo, optimizing storage and retrieval processes.

Worked on Spark GraphX and Neo4j, utilizing Cypher for advanced graph data analysis and visualization. Implemented graph computing solutions through Apache TinkerPop and Gremlin, contributing to sophisticated data relationship insights. Gained deep technical knowledge of Titan for scalable graph storage and Elasticsearch for powerful search and analytics capabilities across multiple datasets.
Big Data Engineer
7/2/2017 - 8/2/2018

Developed proficiency in Hadoop, Hive, Flume, Sqoop, Kafka, Spark, and Linux. Demonstrated technical expertise in Python, Impala, Cassandra, and Pyspark, with a strong focus on Machine Learning. Extensive experience with Data Factory, AWS S3, HD Insight, and Blob Storage. Mastered AWS Athena and contributed to AWS Architecture for Data Lake and Google Architecture for Data Lake.
Big Data Engineer
2/2/2017 - 7/2/2017

Developed proficiency in Hadoop, including advanced utilization of Hive for data query and analysis. Applied Flume and Sqoop for efficient data ingestion and transfer. Leveraged Kafka for real-time data streaming and HBase for scalable, distributed storage solutions. Achieved expertise in Spark for big data processing and analytics, alongside extensive use of Linux for system administration and scripting. Demonstrated technical skills in Java and Python for application development and automation tasks. Utilized Cassandra and MongoDB for handling large-scale, NoSQL database requirements. Employed Talend for data integration and ETL processes. Capably managed data analytics and reporting using Google Analytics, with additional experience in leveraging IBM Watson for AI-driven insights. Effectively used Google BigQuery and Google BigTable for high-performance data warehousing and storage.