Mustafa Yılmaz
tr
Mustafa Yılmaz

Who Is Mustafa Yılmaz?

Software Engineer • Big Data and Data Platforms • Artificial Intelligence

I am a Software Engineer with professional experience in software development, big data, real-time analytics, data platforms, and artificial intelligence across the finance, telecommunications, and technology sectors.

I currently work as a Software Engineer in the Information Technologies division at Borsa İstanbul. My work focuses on large-scale data platforms, real-time data processing systems, analytical infrastructures, and modern data architectures.

I began my career as a software developer and gradually specialized in high-volume data processing, distributed systems, NoSQL technologies, data warehouse and data lake architectures, machine learning, and artificial intelligence applications.

Professional Experience

  • Borsa İstanbul

    I work on big data, real-time data processing, analytical platforms, and distributed data architectures. My responsibilities include developing data platforms and analytical systems that process high volumes of data reliably, efficiently, and at scale. Real-time and batch data processing, modern data architectures, and enterprise data platforms are among my primary areas of focus.

  • Burgan Bank

    I worked on real-time customer analytics, data warehouse, and business intelligence projects. I contributed to real-time systems built with technologies such as Kafka, Kubernetes, MicroStrategy, and analytical data platforms. My work included processing enterprise data, delivering it to analytical systems, and making it available for different business requirements.

  • IDT Corporation – Net2Phone

    I developed data pipelines, Python and Flask-based APIs, microservices, and CI/CD processes running on GCP and AWS. I worked on cloud-based applications, automation of data-processing workflows, and modernization of existing software systems. I also contributed to the migration of applications from Python 2.x to Python 3.x.

  • Turkcell

    I worked on big data, data processing, analytics, and recommendation-system projects in the telecommunications sector. My responsibilities included processing and analyzing high-volume telecommunications data on distributed systems and making this data available to different digital services.

  • VakıfBank

    I worked on enterprise projects focused on big data, data analytics, security, and performance in the banking industry. I gained experience in processing financial data, developing data platforms, and building analytical processes with demanding performance requirements.

Areas of Expertise

Big Data and Distributed Systems

I design and develop scalable data platforms for processing high-volume data through both batch and real-time workflows.

  • Apache Kafka
  • Apache Spark
  • Apache Hadoop
  • Apache Airflow
  • Elasticsearch
  • HBase
  • Distributed data processing
  • Real-time data pipelines
  • Batch data processing
  • Event-driven architectures
  • Change Data Capture
  • Data integration
  • High-volume data processing
  • Performance and scalability

Data Warehouse, Data Lake, and Lakehouse

I work with data warehouse, data lake, and lakehouse architectures to store enterprise data centrally, reliably, and in a way that supports different analytical requirements.

  • Data warehouses
  • Data lakes
  • Lakehouse architectures
  • Apache Iceberg
  • Apache Parquet
  • Trino
  • S3 and S3-compatible object storage
  • Real-time data warehouses
  • Data modelling
  • Historical data management
  • Slowly Changing Dimensions
  • CDC-based data replication
  • Batch and streaming data integration

Databases and NoSQL

I have experience with relational, column-oriented, distributed, and NoSQL data platforms. I believe the right data technology should be selected according to the structure of the data, access patterns, business requirements, and expected performance.

  • SingleStore
  • ClickHouse
  • PostgreSQL
  • Oracle
  • Microsoft SQL Server
  • MySQL
  • Redis
  • Elasticsearch
  • HBase
  • Columnstore databases
  • Distributed databases
  • NoSQL data modelling
  • Real-time analytical databases

Python and Software Development

I primarily use Python for data engineering, API development, automation, data analysis, and artificial intelligence applications. Maintainability, performance, scalability, and code quality are among my primary priorities.

  • Python
  • Pandas
  • Flask
  • C#
  • .NET and .NET Core
  • Java
  • SQL
  • T-SQL
  • PL/SQL
  • REST APIs
  • Microservice architectures
  • Enterprise software development
  • Data-driven application development

Machine Learning and Artificial Intelligence

I combine my data engineering experience with machine learning and artificial intelligence technologies to develop systems that generate meaningful insights from data, and to operate them sustainably in production environments.

  • Machine learning
  • Deep learning
  • Natural language processing
  • Recommendation systems
  • TensorFlow
  • Keras
  • Pandas
  • Data analysis
  • Feature engineering
  • Model development
  • Model integration
  • Prediction and classification problems

Generative AI

I work on integrating generative artificial intelligence technologies into software systems, enterprise applications, and data platforms.

  • Large Language Models
  • Generative AI applications
  • Enterprise AI integrations
  • Data-driven AI applications
  • Prompt engineering
  • AI-powered automation
  • API integrations for artificial intelligence services
  • Combining AI systems with big data platforms
  • Secure use of enterprise data in AI applications

Cloud, Kubernetes, and DevOps

I use modern platform and DevOps technologies to build scalable, portable, and maintainable data and software systems.

  • Kubernetes
  • Docker
  • Google Cloud Platform
  • Amazon Web Services
  • CI/CD
  • Microservices
  • Cloud-native architectures
  • On-premises platforms
  • Hybrid architectures
  • Containerized applications
  • Automation and monitoring processes

My Perspective on Technology

I do not see software development as simply writing code. For me, technology is about understanding the right problem, designing the appropriate architecture, processing data reliably, and building scalable and sustainable solutions. I am particularly interested in the intersection of big data, real-time analytics, NoSQL, data lakes, machine learning, and generative artificial intelligence. Instead of only following new technologies, I prefer to learn by applying them to real systems and adapting them to enterprise requirements. I see software development and artificial intelligence as a continuous journey of learning and improvement. Through this blog, I share the technical challenges I encounter, the solutions I develop, data architecture practices, and my experience in technology.