Eduardo Bernad

• • Designed and developed the company's core ETL system powering Data Science and Machine Learning teams.

• • Built scalable pipelines on AWS Batch and Postgres within a Dockerized environment.

• • Ensured reliability and automation through TeamCity CI/CD integration and AWS ECR. Python, AWS (Batch, EC2, Postgres, Docker), GitHub, TeamCity, Jira

• • Re-architected the company's entire ETL ecosystem, replacing costly Glue and EMR jobs with efficient ECS-based solutions, reducing infrastructure costs by over 50%.

• • Designed and implemented a new company-wide data core model, consolidating al the external data sources into a unified layer in S3/Athena.

• • Leveraged DBT and Apache Iceberg to build a scalable, consistent data model accessible across teams including Data Engineering, Analytics, Data Science, and BI.

• • Introduced Prefect as a modern orchestration framework to manage all the daily and hourly ETL pipelines, improving observability and reliability.

• • Led the development of dashboards for teachers and students within the Santillana Global education platform.

• • Designed and implemented data transformations to derive insights and improve learning outcomes.

• • Maintained client communication and ensured AWS-based solutions met scalability requirements.

Technologies: AWS (Lambdas, Glue, S3, DynamoDB, Redshift), Spark, Python, Stash, Bamboo