Istanbul Technical University, Data Engineer #opensource, #dataengineering, #bigdata, #etl, #datapipeline
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Assessing your cultural and operational fit
Mediastream AG
Data Scientist
June 26, 2026 – Present
elk-stack-mastery
October 17, 2024 – November 4, 2024
A comprehensive project focusing on setting up and configuring the Elastic Stack (Elasticsearch, Logstash, and Kibana) for efficient log management and analytics. This project includes Elasticsearch configurations, Logstash pipelines, and Kibana visualizations, with detailed step-by-step documentation.
View Projectreal-time-data-pipeline-kafka-mongo-elasticsearch-pyspark
October 3, 2024 – October 4, 2024
A real-time data pipeline project using Kafka, MongoDB, Elasticsearch, and PySpark. Streams raw data from Kafka, enriches it with sentiment analysis using Hugging Face models, stores results in MongoDB, and visualizes data in Elasticsearch with Kibana. Scalable solution for real-time data analytics and machine learning.
View ProjectRedditDataPipeline
September 8, 2024 – September 8, 2024
Data Engineering with Reddit Api, Airflow, Hive, Postgres, MinIO, Nifi, Trino, Tableau and Superset
View Projecte2e-otp-pipeline
August 6, 2024 – August 8, 2024
End to End OTP Pipeline Project using Docker, Airflow, Kafka, KafkaUI, Cassandra, MongoDB, EmailOperator, SlackWebhookOperator and DiscordWebhookOperator
View Projecte2e-structured-streaming
July 25, 2024 – July 26, 2024
End-to-end data pipeline that ingests, processes, and stores data. It uses Apache Airflow to schedule scripts that fetch data from an API, sends the data to Kafka, and processes it with Spark before writing to Cassandra. The pipeline, built with Python and Apache Zookeeper, is containerized with Docker for easy deployment and scalability.
View ProjectUdacity-Data-Pipeline-with-Airflow
July 14, 2024 – August 13, 2024
Udacity Data Engineering Nanodegree Program, Data Pipeline with Airflow project using MinIO and Postgresql.
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate a strong passion for data engineering and data science, aligning well with a culture that values continuous learning and practical application. The diversity of tools and technologies explored (Kafka, Spark, Airflow, Cassandra, MongoDB, Elasticsearch, Hugging Face, Docker, etc.) indicates a broad interest and adaptability. However, the lack of team-based projects or collaborative experience in the provided data limits the assessment of cultural fit in a team environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and hands-on approach to learning and implementing complex data systems. The focus on end-to-end pipelines suggests an understanding of operational aspects. However, without psychometric test results or interview data, a comprehensive assessment of soft skills and operational fit is limited.