Achraf Briki

Built a CDC platform with PostgreSQL, Debezium, Kafka Connect, Schema Registry, Flink and Spark, then industrialized data flows with Airflow/Dagster, dbt and Airbyte. Structured the Bronze/Silver/Gold lakehouse on S3/MinIO with Delta Lake, Iceberg/Hudi, Databricks/Snowflake and DataHub/OpenMetadata, reporting 60% faster.

Developed a Python gateway on Raspberry Pi/Linux to collect, normalize and forward biometric events via REST and asynchronous messaging. Made the pipeline reliable with MongoDB/PostgreSQL, Pandas, Parquet, Docker, tests and CI/CD, reducing data inconsistencies by 15%.

Turned .NET/C# and REST actions into structured events, then improved analytics reliability with SQL/Python, dbt and incremental ingestion. Added OpenTelemetry to improve auditing, diagnostics and visibility into bottlenecks and incidents.

Implemented first-party tracking with Python, SQL and Pandas, then checked event consistency, completeness and deduplication. Built datasets, funnels and acquisition/engagement/conversion KPIs, increasing analytics visibility by 25% in two months.

Consolidated financial, enrollment and activity data with Python, SQL, MongoDB and PostgreSQL to replace manual reporting. Prepared historical data in Parquet, with a path to AWS S3/Glue Data Catalog and automated aggregations, improving KPI consistency.

Erasmus+ exchange program in Artificial Intelligence, expected to complete in June 2027.

Pursuing an Engineering Degree in Artificial Intelligence, currently ongoing.

Bachelor's Degree in Information Systems Development.