Senior Data Engineer

Panthr; Madrid; Presencial; EUR 50.000 - 80.000; Jornada completa

Descripción de la vacante

A leading company is seeking a Senior Data Engineer to build scalable ML pipelines and production-grade systems. The ideal candidate will have deep expertise in AWS and machine learning, with a focus on delivering real-time insights across various business domains. This role requires strong collaboration skills and the ability to work independently in a remote setting.

Formación

• 5+ years of professional data engineering experience.
• Deep hands-on experience with AWS cloud services.
• Strong skills in Python and SQL.

Responsabilidades

• Design and implement scalable data pipelines on AWS.
• Operationalize machine learning models in production environments.
• Collaborate with cross-functional teams.

Conocimientos

AWS

Python

SQL

MLOps

Data Governance

Problem Solving

Communication

Herramientas

Glue

SageMaker

Docker

Terraform

Kafka

Airflow

Descripción del empleo

We are the first zero-BS talent matchmaker. Empowering individuals through their job seeking journey whilst finding the perfect candidate that fits not only a role but a company vision.

From start to finish, we focus on making the recruitment process smooth and positive for everyone involved.

With more than 15 years of experience in the field, we make use of real data insights, professional expertise and technology. Although we offer worldwide service, our feet are always on the ground and trust is at the heart of what we do, built on transparency and a genuine commitment to seeing you succeed.

Meet our client

Our Client is CONFIDENTIAL

About the role

A forward-thinking organization is seeking a Senior Data Engineer with deep AWS and machine learning infrastructure expertise. This is a hands-on contract role focused on building scalable ML pipelines and production-grade systems that deliver real-time insights and advanced analytics across various business domains.

Key Responsibilities

• Design and implement scalable, secure, and automated data pipelines on AWS using services like Glue, Lambda, Step Functions, S3, Redshift, etc.
• Operationalize machine learning models in production environments, leveraging SageMaker or custom deployment frameworks.
• Build and automate ETL / ELT workflows for both structured and unstructured data.
• Apply MLOps best practices to support rapid iteration and deployment of ML models.
• Collaborate with cross-functional teams, including data scientists, architects, and business stakeholders.

Mandatory Requirements

• 5+ years of professional data engineering experience, with at least 2 years in a senior-level role.
• Deep hands-on experience with AWS cloud services, including Glue, Lambda, Redshift, S3, SageMaker.
• Strong skills in Python and SQL; PySpark experience is a bonus.
• Knowledge of containerization (Docker), orchestration tools (Airflow, StepFunctions), and infrastructure-as-code (Terraform, AWS CDK).
• Experience deploying and managing machine learning models at scale.
• Real-time data streaming using Kafka or Kinesis.
• Familiarity with data governance and cloud security best practices.
• Previous work in regulated industries such as finance or healthcare.
• Strong analytical and problem-solving mindset.
• Excellent communication and team collaboration abilities.
• Capable of working independently in a remote setting while aligning deliverables with business goals.