Data Engineer (AWS)

TL;DR

Data Engineer (AWS): Designing, building, and operating robust, scalable, and secure data platforms in AWS cloud environments with an accent on end-to-end data lifecycle management. Focus on developing ETL/ELT pipelines, optimizing cloud-native data solutions, and implementing CI/CD and IaC practices.

Location: Hybrid: Lisboa - Expo, VNG - Cais Gaia (Portugal)

Company

hirify.global is an AI-powered global business and technology transformation partner delivering end-to-end services and solutions across various industries.

What you will do

• Design, develop, and optimize ETL/ELT data pipelines using Python, SQL, and Spark.
• Build and maintain cloud-native data solutions leveraging AWS Glue, Redshift, Athena, EMR, S3, and Lambda.
• Orchestrate and monitor data workflows using AWS Step Functions, Airflow, Prefect, or Dagster.
• Implement and maintain CI/CD pipelines and Infrastructure-as-Code (IaC) practices.
• Collaborate with cross-functional stakeholders to translate business requirements into scalable technical solutions.
• Apply and enforce data security best practices, including IAM policies and encryption.

Requirements

• Proven experience as a Data Engineer working in AWS cloud-based data platforms.
• Strong proficiency in Python, SQL, and Spark for data processing and transformations.
• Hands-on experience with AWS Glue, Redshift, Athena, EMR, S3, and Lambda.
• Experience with data orchestration tools (Step Functions, Airflow, Prefect, or Dagster).
• Knowledge of containerization and orchestration technologies (Docker, Kubernetes, ECS).
• Familiarity with CI/CD pipelines and modern DevOps practices.

Nice to have

• GenAI expertise.
• AWS certifications such as AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect.
• Experience with Machine Learning and AI/ML data pipelines in AWS.
• Knowledge of serverless data engineering with Lambda and API Gateway.
• Hands-on experience with NoSQL databases (DynamoDB, MongoDB, OpenSearch).

Culture & Benefits

• Hybrid work model.
• Multicultural and inclusive team environment with a supportive atmosphere.
• Access to training and certification programs.
• Health and life insurance.
• Referral program with bonuses for talent recommendations.
• Clear career growth paths and professional development programs.