(Senior) AWS Data Engineer

- Please note: we are only looking for candidates that are (already) based in the Netherlands! Not based in the Netherlands? Your application won’t be considered. -

What impact will you make today as (Senior) AWS Data Engineer at Eraneos?

At Eraneos, we activate data and use AI to create real value for our customers. Are you up for a new data driven challenge? Become a (Senior) AWS Data Engineer with us!

Join our Data & AI team and you get to work with the brightest data engineers and bring innovative ideas to life. Our team is driven by creating technical & innovative solutions that make an impact at our customers. We aim to go the extra mile and help our customers become more data driven and get valuable results.

In your role as (Senior) AWS Data Engineer you will be working in a dynamic role that puts you in the position of a technical lead responsible for implementing our solutions together with a team of data engineers and data scientists. In this position you will be working with a focus on AWS and our Data Hub and Applied AI solutions. You will get the best algorithm into production, design user stories before implementation, develop data structures and data pipelines.

Tasks & responsibilities

• Design and implement scalable, robust, and high-performance data architectures that meet business requirements.
• Provide technical leadership and guidance to junior data engineers, educate them on best practices and give support to their professional development.
• Work closely with cross-functional teams including data scientists, analysts, and business stakeholders to understand their needs and deliver effective data solutions.
• Build and maintain data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
• Include and implement data quality checks and validations in your data pipelines to ensure accuracy, completeness, and consistency of data.
• Build and maintain strong relationships with stakeholders, fostering trust and understanding to effectively deliver data solutions that align with business goals.
• Identify and optimize performance bottlenecks in data pipelines and storage systems to improve throughput, latency, and resource utilization.
• Evaluate new technologies, tools, and frameworks in the data engineering space, and make recommendations for adoption based on business needs and technical feasibility.
• Implement and optimize continuous delivery pipelines for data engineering workflows, enabling rapid and reliable deployment of data solutions.
• Collaborate with sales and account management teams to understand client requirements, propose data solutions, and contribute to business development efforts.
• Ensuring data security, privacy, and compliance with relevant regulations by implementing appropriate security measures and access controls.
• Design and implement cloud infrastructure solutions using tools such as Terraform, ARM templates, AWS CloudFormation, or AWS Cloud Development Kit.

Where, what & with whom?

Eraneos group is an international group with more than 1000 employees, providing complementary consulting and implementation expertise. We drive our clients' digital transformation in an even more targeted and comprehensive manner.

In your role as (Senior) AWS Data Engineer you will be part of the Eraneos Data & AI team in the Netherlands. We combine business understanding, technical knowledge, extensive experience, and our innovative mindset to activate data and turn it into actual value. We are driven by achieving meaningful results and dedicated to unleashing the full potential of digital, and the full potential of Data & AI.

We advise on, design, build, and deliver Data & AI solutions. Our team consists of consultants, data architects, data scientists, data engineers, software engineers and project managers. These professionals each have their own expertise, but also share a passion for solving data problems and innovating. We can handle any data & AI challenge, end-to-end, full-stack, using technologies like Kubernetes, Spark, Kafka, Scikit learn and Cloud-native components (Azure and AWS) and development languages like Java or Python.