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Riahi IT Solutions

AWS Data Engineering Consultant

CV

Cloud and data engineer with hands-on experience designing, building, and operating data platforms on AWS. Specialized in ETL/ELT, modern data warehousing, and infrastructure-as-code with Terraform, delivering scalable pipelines and analytics solutions for automotive and home appliances use cases.

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Skills

Programming

Python, C/C++, Scala, Java, SQL, JavaScript, Kotlin, LaTeX, R, Object-oriented programming

Data Engineering & Big Data

Apache Spark, Apache Hudi, Apache Iceberg, Delta Lake, Apache Kafka, PostgreSQL, MySQL, MongoDB

Cloud & DevOps

AWS, Databricks, Terraform, CI/CD (GitHub Actions, Bitbucket, Bamboo), Docker, Kubernetes, Linux, Git

Data Science & ML

Machine learning, Applied regression, Data visualization (dplyr), Deep learning, PyTorch

Web

FastAPI, NodeJS, ReactJs, HTML5, CSS

Tooling & Practices

Bash scripting, GitHub workflow, Ansible, Slurm, Unit testing

Languages

English (fluent), French (advanced), German (advanced), Arabic (native)

Industry

Automotive, Home appliances

Certifications

11/2024

AWS Certified Solutions Architect – Associate

Amazon Web Services

View certificate

Experience

07/2024 – Present

Data Engineer · Data Reply (Consultancy)

Munich, Germany · Confidential premium automotive manufacturer (Germany)

  • Manage and optimize cloud infrastructure on AWS with a strong focus on automation, scalability, and cost efficiency using Terraform.
  • Develop and maintain dbt models and integrate them with GitHub Actions to build automated deployment pipelines.
  • Design end-to-end data flows where data is ingested into Amazon S3, processed using AWS Glue and Step Functions, and exposed via Amazon QuickSight dashboards.
  • Leverage Python, SQL, and AWS services (Glue, Step Functions, Lambda, Athena) throughout the data and analytics stack.
  • Integrate with Azure APIs/UIs for cross-cloud collaboration and implement email alerting for spend thresholds.
  • Implement a cloud efficiency score from scratch by merging sources across cloud accounts to provide recommendations per account and department.
  • Implement a daily Teams report that aggregates errors across project resources (Lambda, SQS, Step Functions).

Tech: AWS, Python, CI/CD, GitHub, ECS, Step Functions, Lambda, dbt, SQL, QuickSight, Glue, Athena, Terraform

Internal projects

  • Implement demos using industrial data platforms (HighByte for data modeling/integration, Litmus for edge connectivity and device management).
  • Deploy end-to-end industrial analytics solutions on AWS (EC2, S3, Glue, Athena, QuickSight, Grafana).
  • Contribute to white papers and RFPs, supporting solution design and technical positioning.
  • Deliver internal and client-facing presentations on data platforms, cloud architectures, and best practices.

Tech: HighByte, Litmus, AWS (EC2, S3, Glue, Athena, QuickSight, Grafana, Lambda, Step Functions), Python, Terraform

10/2021 – 06/2024

Working Student: Data Engineer · Data Insights GmbH (Consultancy)

Munich, Germany · Confidential multinational home-appliances manufacturer

  • Manage AWS accounts and underlying infrastructure for data platforms used in production.
  • Reduce technical debt by fixing code smells and improving reliability in Scala, Java, and Python services.
  • Build and maintain data pipelines and CI/CD workflows using Bitbucket, Bamboo, and Gradle for multiple applications.
  • Implement generic Gradle build automation and parameterized templates to standardize CI/CD across applications.
  • Improve EMR performance by orchestrating parallel execution via AWS Step Functions.

Tech: AWS, Java, Scala, Gradle, Python, CI/CD, Bitbucket, Bamboo, EMR, Step Functions, Terraform

Internal projects

  • Compare Apache Iceberg, Apache Hudi, and Delta Lake; develop a unified API for common operations across all three table formats.
  • Deploy on AWS EMR and benchmark using Spark History Server; summarize results in an internal blog post.
  • Support AWS account migrations and help design secure, automated infrastructure with Terraform.
  • Develop a utilization forecast application to estimate consultant capacity, expenses, and profit/loss scenarios.
  • Rebuild the utilization forecast as a full web application to replace a Power Apps prototype and improve maintainability.

Tech: Scala, Java, MySQL, JavaScript, EJS, CSS, HTML, NodeJS, Express, Azure AD, Kafka, Spark, Hudi, Iceberg, Delta Lake, AWS, Databricks, Git, SBT, Terraform, Power Apps, Power Automate, Excel

Education

10/2022 – 06/2024

M.Sc. Data Engineering and Analytics

Technical University of Munich · Munich, Germany

  • Grade: 2.0

10/2019 – 09/2022

B.Sc. Computer Science

Technical University of Munich · Munich, Germany

  • Grade: 2.0

09/2014 – 06/2017

High school diploma in Mathematics

Pioneer School of Ariana · Ariana, Tunisia

  • Grade: 16.83/20 (German Grading System: 1.86)