Senior Data Engineer (Python/Databricks/Spark) - Full Remote Portugal
ABOUT THE OPPORTUNITY
We are looking for a Senior Data Engineer to join an international technology-driven environment focused on building scalable, high-performance data platforms that support impactful digital products used worldwide. This role is ideal for professionals passionate about modern data engineering, cloud ecosystems, distributed systems, and building reliable data solutions in collaborative Agile environments.
As a Senior Data Engineer, you will play a strategic role in designing and implementing scalable data architectures, developing robust ETL pipelines, and supporting advanced analytics initiatives across multiple cloud platforms. Beyond technical delivery, you will collaborate closely with engineering leadership, stakeholders, and cross-functional teams, contributing to architectural decisions, engineering best practices, and continuous improvement initiatives.
The company promotes a collaborative engineering culture built around autonomy, innovation, knowledge sharing, and technical excellence.
PROJECT & CONTEXT
You will work on modern cloud-native data platforms supporting both real-time and batch processing workloads. The environment leverages technologies such as Databricks, Apache Spark, Apache Airflow, Python, dbt, Kafka, Docker, and Kubernetes across multi-cloud ecosystems including AWS, Google Cloud Platform (GCP), and Azure.
The engineering teams operate using Agile methodologies and modern DevOps practices, with strong focus on automation, scalability, CI/CD workflows, data modeling, and observability. Projects involve designing end-to-end data pipelines, building optimized OLAP systems, and enabling scalable analytics platforms for complex business domains.
WHAT WE'RE LOOKING FOR (Required)
- Minimum 5 years of professional experience as a Data Engineer
- Strong hands-on experience with Python
- Advanced SQL skills for large-scale data processing
- Strong experience with Databricks and Apache Spark
- Experience designing and maintaining ETL pipelines using dbt
- Experience with Apache Airflow for orchestration and workflow automation
- Hands-on experience with cloud platforms including AWS, GCP, or Azure
- Experience with AWS S3, Google BigQuery, Google Cloud Storage, or Azure Databricks
- Knowledge of Infrastructure as Code (IaC) using Terraform
- Experience with event-driven or streaming technologies such as Apache Kafka
- Experience with Docker and Kubernetes
- Strong understanding of dimensional data modeling methodologies including Kimball
- Experience designing OLAP systems, Star Schemas, and Semantic Models
- Understanding of data architecture methodologies such as Inmon and Data Vault
- Experience with CI/CD workflows and Git version control
- Strong communication and collaboration skills
- Ability to work closely with technical and non-technical stakeholders
- Fluency in English
NICE TO HAVE (Preferred)
- Experience with search technologies or search platforms
- Exposure to multi-cloud enterprise data ecosystems
- Experience building real-time analytics or streaming platforms
- Knowledge of observability and monitoring practices for data systems
- Experience mentoring engineering teams or guiding technical decisions
- Familiarity with performance optimization for distributed data processing workloads
- Experience working in international and cross-functional Agile teams
- Interest in scalable architecture, automation, and modern data platform innovation
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