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Lorena Kouam

@lorenakouam

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Passionate data engineer with expertise in building scalable data pipelines.

France

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What I'm looking for

I seek a role that fosters innovation and collaboration, with opportunities for growth and skill development.

With over five years of experience in data engineering, I specialize in building robust, scalable, and automated data pipelines using the Modern Data Stack. My journey has taken me through various roles, where I have successfully migrated critical data infrastructures and optimized performance for leading companies like Decathlon and Michelin. I am passionate about sharing my knowledge through Medium articles and LinkedIn posts, actively engaging with industry trends and best practices.

Throughout my career, I have developed a strong technical foundation, implementing advanced Spark optimization techniques and CI/CD pipelines to enhance data processing efficiency. My experience includes mentoring teams on dbt and Databricks, ensuring that best practices are adopted across organizations. I thrive in collaborative environments and am committed to continuous learning and improvement, both for myself and my teams.

Experience

Work history, roles, and key accomplishments

Data Engineer

Decathlon Germany

Aug 2022 - Present (2 years 11 months)

Implemented data pipelines within an existing Lakehouse architecture (Bronze/Silver/Gold medallion) and analyzed the existing system, auditing over 50 Redshift pipelines to identify dependencies. Migrated and adapted more than 50 legacy pipelines to different Delta Lake layers using dbt or PySpark, based on complexity.

Databricks Delta Lake DBT Pyspark Airflow GitHub Actions AWS SQL

Data Engineer

Michelin France

Apr 2022 - Present (3 years 3 months)

Mentored teams on advanced dbt usage, including modeling, testing, and documentation, while addressing specific technical needs and resolving complex blockers. Developed Proofs of Concept (PoCs) to demonstrate advanced dbt capabilities and benchmarked orchestration solutions like Airflow, Dagster, and Prefect through practical PoCs.

DBT Airflow Dagster Prefect Python SQL Great Expectations Elementary

Data Engineer

PSA Banque

Oct 2021 - Present (3 years 9 months)

Developed and optimized Spark pipelines using PySpark for processing large volumes of financial data, ensuring high availability and performance. Built new data pipelines to meet evolving business requirements and performed preventive and corrective Data Lake maintenance, including performance monitoring and troubleshooting.

Apache Spark SQL DBeaver Python Data Lake Performance Monitoring

Data Engineer

Depiltech

Apr 2021 - Present (4 years 3 months)

Designed an AWS serverless platform using Lambda, Glue, S3, and Tableau, complete with automated ELT pipelines. Developed over 15 data pipelines for CRM and ERP systems, integrating heterogeneous sources and implementing dimensional modeling.

AWS Lambda AWS Glue Amazon S3 Tableau CloudFormation Python SQL Redshift

Big Data Engineering Apprentice

Thales Alenia Space

Oct 2018 - Present (6 years 9 months)

Trained in software engineering and data processing within a space environment, acquiring foundational knowledge in DevOps and software quality. Gained practical experience with technologies such as Java, Drools, Git, Sonar, and Artifactory.

Java Drools Git Artifactory Software Engineering Data Processing DevOps

Education

Degrees, certifications, and relevant coursework

ESIGELEC

Engineering Degree, Big Data for Digital Transformation

Completed an Engineering Degree with a specialization in Big Data for Digital Transformation. Focused on acquiring skills in data engineering and related technologies.