Data Engineer II, Managed Operations Engineering & Data Science (MOEDS)

Amazon; Asti; In loco; EUR 45.000 - 70.000; Tempo pieno

Descrizione del lavoro

A leading cloud computing company in Piemonte, Italy is seeking a Data Engineer II to support projects improving operational efficiency and customer experience. The role involves collaborating with business and software teams, developing data models, and maintaining data pipelines. Ideal candidates will have extensive experience in data engineering, familiarity with AWS technologies, and a passion for impactful data solutions.

Servizi

Advanced tech stack

Collaborative environment

Opportunity for professional growth

Competenze

• 3+ years of data engineering experience required.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Knowledge of distributed systems as it pertains to data storage and computing.

Mansioni

• Collaborate with software teams to design systems.
• Develop robust data models for data-driven initiatives.
• Design maintainable and scalable data pipelines.

Conoscenze

Data modeling

ETL pipeline building

Distributed systems knowledge

Python

Analytical problem-solving

Strumenti

AWS Glue

Apache Airflow

Redshift

S3

Descrizione del lavoro

Overview

Data Engineer II, Managed Operations Engineering & Data Science (MOEDS) — AWS

Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable cloud infrastructure. This role supports MOEDS, a group focused on reducing operational load and toil through long-term engineering projects that improve availability, reliability, latency, performance, and efficiency for AWS Regions. This position requires that the candidate selected be a U.S. Citizen.

Key responsibilities

• Collaboration and Product Development: Interact with business and software teams to understand their requirements and operational processes to inform system design
• Data Modeling and Architecture: Develop robust data models and architectures to support data-driven initiatives, ensuring data quality, consistency, and accessibility
• Data Pipeline Development: Design, build, and maintain scalable and reliable data pipelines to ingest, transform, and load data into a unified data platform
• Scalability and Performance: Design and implement scalable data solutions that handle increasing data volumes and support high-performance data access and querying
• Documentation & Continuous Improvement: Create, enhance, and maintain technical documentation

A day in the life

Work in a state-of-the-art innovation lab within AWS, pushing the boundaries of cloud management through long-term engineering initiatives. Join Data Science & Data Engineering teams in leveraging advanced analytics, machine learning, and artificial intelligence to inform high-impact investment decisions and reduce operational toil. The Data Engineering team focuses on democratizing data and delivering highly scalable, highly available solutions for customers.

What we offer

• Advanced tech stack including big data technologies (e.g., AWS Glue, Apache Airflow), AI/ML, and cloud-native tools (CloudFormation)
• Opportunity to work on projects that impact millions of AWS customers
• Collaborative environment with leaders in cloud computing and data science
• Opportunity to shape the future of cloud operations and set industry standards

About the team & AWS

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We foster a culture of inclusion and continuous learning. AWS Utility Computing (UC) provides innovations across compute, database, storage, IoT, platform, and productivity apps, including security-focused solutions.

Inclusive Team Culture: Our employee-led affinity groups foster inclusion and ongoing learning experiences. Work/Life Balance: We value flexibility and support in the workplace and at home. Mentorship & Career Growth: We provide knowledge-sharing, mentorship, and resources to help you develop professionally. Diverse Experiences: We encourage applicants with non-traditional backgrounds to apply.

BASIC QUALIFICATIONS

• 3+ years of data engineering experience
• Experience with data modeling, warehousing, and building ETL pipelines
• Knowledge of distributed systems as it pertains to data storage and computing
• Experience in at least one modern scripting or programming language (Python, Java, Scala, or NodeJS)

PREFERRED QUALIFICATIONS

• 5+ years of data engineering experience
• Experience building/operating highly available, distributed data extraction, ingestion, and processing systems
• Experience with non-relational databases/data stores (object storage, document/key-value stores, graph databases, column-family databases)
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles/permissions

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require accommodations during the application or hiring process, including interview or onboarding support, please visit amazon.jobs/accommodations for more information.