Data Engineering AWS/GCP
Mid-level Data Engineer (Team Lead/Consultant) role in Amsterdam, building and optimizing scalable data pipelines and architectures on AWS and GCP for Fortune 500 clients, working across big data analytics, machine learning, and serverless computing.
- Compensation
- Not disclosed
- Location
- Netherlands
- Work setup
- Not specified
- Seniority
- Middle
- Employment
- Full time
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Mid-level data engineering experience
- Experience building and optimizing data pipelines and architectures on AWS and GCP
Nice to have
- Skills in big data analytics, machine learning, and serverless computing
- Ability to lead and contribute to data engineering projects as a Team Lead/Consultant
Full description
Job Description
Do you see challenges as opportunities? At Accenture, we’re looking for talented Data Engineers who are ready to reshape industries with cloud-driven solutions. By working with Fortune 500 clients, leveraging AWS, GCP, and the latest data technologies, you’ll be at the forefront of innovation, solving real-world problems and driving impactful change.
- Data Engineering AWS/GCP
- Data Eng, Mgmt & Governance Team Lead/Consultant
- Mid-Level
- Full time
- Amsterdam
How we innovate at Accenture
Our teams work at the intersection of innovation and practicality, using the latest tools to tackle challenges that truly matter. Whether it’s enabling businesses to thrive in a fast-changing digital landscape or addressing global issues with innovative solutions, our focus is on creating impact and driving progress. By joining our team, you’ll collaborate with talented minds and industry leaders to shape the future in ways that are meaningful, sustainable, and forward-thinking.
What you’ll do:
- Build and optimize resilient, scalable data pipelines and architectures on AWS and GCP.
- Develop innovative solutions to provide actionable insights for tackling complex business challenges.
- Lead and contribute to projects leveraging cutting-edge technologies in big data analytics, machine learning, and serverless computing.
- Stay ahead of the curve by experimenting with and integrating emerging trends and tools in the data engineering space.