Senior Data Engineer: AWS & GCP for Life Sciences Platform

Reach IT; Portugal; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

Reach IT is seeking a Senior Data Engineer to join a Life Sciences data engineering project supporting a pharmaceutical organization focused on research, development and manufacturing of innovative therapies.

The role centers on building and evolving an enterprise cloud data platform that integrates research, laboratory, manufacturing and operational datasets to power analytics, data quality and scientific decision-making, using AWS, GCP, Python, SQL and PySpark.

Formación

• Senior Data Engineer with AWS and GCP experience.
• Experience building enterprise cloud data platforms.
• Background in data ingestion, processing and analytics.

Responsabilidades

• Develop AWS ingestion and processing pipelines using S3, Glue and EMR.
• Implement GCP analytics pipelines with Cloud Storage, Dataflow and BigQuery.
• Create Python, SQL, and PySpark transformations to standardize data.
• Design ETL workflows and manage schema evolution and loads.
• Configure AWS Step Functions and Airflow for pipeline orchestration.
• Improve Spark and BigQuery performance, reduce costs.
• Enforce data quality checks and governance with Glue Data Quality and Dataplex.
• Automate cloud infrastructure and data pipeline deployments with Terraform and GitHubActions.
• Collaborate with Data Architects, Analytics Engineers, and pharma teams.

Conocimientos

ETL pipeline design

Data governance awareness

Performance optimization

Herramientas

AWS

GCP

Python

SQL

PySpark

ETL pipelines

Data Lake & Data Warehouse architectures

Apache Airflow

Terraform

Git & GitHub Actions

Descripción del empleo

Reach IT is seeking a Senior Data Engineer to join a Life Sciences data engineering project supporting a pharmaceutical organization focused on research, development and manufacturing of innovative therapies.

The role centers on building and evolving an enterprise cloud data platform that integrates research, laboratory, manufacturing and operational datasets to power analytics, data quality and scientific decision-making, using AWS, GCP, Python, SQL and PySpark.