Wael HILATI

DATA ENGINEER

SKILLS

Techniques

•BigData : Hadoop (MapReduce, Yarn, HDFS), Hive, Hbase, Kafka, Spark, Sqoop, Flume, MongoDB.

•Machine Learning

•Languages: Java, Scala, Python, C.

•Data base: MySQL.

•Web development: HTML, CSS, PHP.

•Data indexing: Elasticsearch.

•Continuous integration: Maven, SBT, Git.

Languages

•French: Fluent

•English: Good

Methodology

•Agile SCRUM

Certifications

•Machine Learning from Stanford University (Coursera)

•Reinforcement Learning from the School of Advanced Studies in Economic Sciences (Coursera)

EXPÉRIENCE PROFESSIONNELLE

PROFESSIONAL EXPERIENCE (France) « Spark-etl » :

Project

Development of a generic Data Ingestion Framework based on the notion of datasets (Spark 2.x) to avoid repetitive tasks for developers.

Achievements

•Establishment of the work environment (installation and configuration of the technical base: hadoop cluster and development and deployment tools)

•Development of the input part from Hbase, HDFS, Hive by transforming data under the Dataset type.

•Development of a data search engine (In progress)

•Development of the output part Hbase, ElasticSearch… (In progress)

Environment

Kafka, Flume, Hbase, HDFS, Spark, Java 8.

Lansrod (France)– Internship : 2019 (6 mois)

Project

Implementation of a Big Data cluster and implementation of a data ingestion system.

Context

Set up a Big Data cluster which enables Big Data analyzes based on new technologies and the creation of an application to study the performance of commercial airlines in the United States and the causes of delays in flights from the analysis of their details.

Achievements

• Establishment of the work environment (installation and configuration of the technical base: hadoop cluster and development and deployment tools)

• Data preparation: Loading of data stored from csv files in Kafka topics

• Data ingestion: Data consumption and storage by Flume in HDFS

• Data cleaning: Removal of duplicates and null values using Spark

• Data storage: Storage of processed data in parquet format

•Data analysis :

Find the most efficient company

Find the best time of day / day of week / time of year to minimize flight delays

Study the effect of the age of the aircraft on flight delays

Environment

Intellij, Java8, Git, Kafka, Spark, ElasticSearch, Flume, Hadoop, Sqoop, Hbase.

IRISA (France) – Engineer internship: 2018 (3 mois)

Project

Apply Reinforcement Learning theory to the field of IOT in order to optimize the consumption of energy recovered by the sensors.

Keywords: Neural network, Monte Carlo, TD learning, Machine learning.

Context

In the field of IOT, the quality of service is directly linked to the frequency of information sent by the sensors. However, this process is costly energy, that's why we implemented the RL to know the optimal frequency depending on the battery level.

Environment

Python, C, Code composer, Git.

Education

Sep 2019 Graduation from Polytechnic Engineer School

« TPS » Tunisia Polytechnic School.

June 2016 Admission to the Tunisian entrance exam to the engineering schools

Rank: 05/1400, Section: Physics-Techniques.

Preparatory Institute for Engineering Studies of Nabeul IPEIN, Tunisia.

June 2014 Scientific Baccalaureate, Section: Techniques.

Bettoumi college, Tunisie.

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