ARAVIND CHENNURI

• Strategic and results-driven Data Engineer with over 7 years of hands-on experience in analytics, business intelligence, and data science across diverse industries, including Ecommerce, Retail, Telecom, and Information technology. 
• Extensive hands-on experience with Google Cloud Platform (GCP) services, Amazon Web Services (AWS) including BigQuery, Google Pub/Sub, Data Form, Data fusion, Cloud Composer, Dataproc, and Dataflow.
• Strong foundation in BigQuery and Teradata, excel in data migration, transformation, and integration processes 
• Skilled in implementing DevOps practices, utilizing orchestration tools like Apache Airflow (DAGs), and optimizing data processing and query performance using technologies such as GCS, Data Proc, and BigQuery.
• Strategic and results-driven hands-on experience in Analytics, Business intelligence, and Data science. Proficient in translating complex datasets into actionable Insights to drive Strategic decision-making.
• Strong understanding of Data governance principles and proven experience in designing scalable data systems while enforcing data governance frameworks. 
• Adept at driving Automation initiatives, collaborating with cross-functional teams, mentoring junior engineers, and staying updated with the latest industry trends.
• Adept in utilizing SQL (including complex stored procedures, views, and functions), Python, Google BigQuery, Google Analytics, Adobe Analytics, and BI/Reporting Tools such as PowerBI, Looker, and Tableau. 
• Hands-on experience with GCP Services, GCS, S3, DynamoDB, Kinesis, Redshift, and EMR to build real-time and batch data pipelines using Apache Airflow (DAGS).
• Proven ability to design and implement Advanced Analytics Dashboards, ensuring real-time visibility into critical metrics. Expertise extends to statistical analysis using Python and R, elevating data-driven strategies.
• Experience with Big Data Architecture and Frameworks, such as Hadoop, involving Hadoop Distributed File System and its components such as PySpark, Hive, Sqoop, MapReduce frameworks, and Hue.
• Knowledge of Amazon Web Services (AWS) services such as S3, EC2, Glue, AWS Lambda, Athena, AWS Step Function, and Redshift.
• Working knowledge of NO SQL databases and their interaction with HBase and Dynamo DB.
• Worked with Airflow scheduling and locking tools to schedule and arrange job workflows.
• Knowledge of Microsoft Azure services including Streams Analytics, ADW, HDInsight cluster, and Azure Data Factory.
• Worked on developing ETL processes on Azure utilizing Azure data bricks and Data Factory.
• Previous experience writing Spark apps in Python.
• Previous experience fine-tuning and debugging spark programmers with optimization approaches.
• Used Sqoop to import and export data from RDBMS to HDFS, Hive, and vice versa.
• Knowledge of the Hive query language, as well as performance optimization techniques like static partitioning, dynamic partitioning, bucketing, and parallel execution.
• Created UDF and UDAF functions and used them in Hive queries.
• Knowledge of MapReduce and the Apache Hadoop API for analyzing structured and unstructured data.

EDUCATION:

Master’s in Data Engineering Analytics.

University of North Texas | Denton, Texas.

Bachelor’s in Computer Science and Engineering.

Jawaharlal Nehru Technological University Hyderabad| College of Engineering Hyderabad (Autonomous)

Kukatpally, Hyderabad, Telangana India.