Data engineer in high-scale systems

Описание:

Are you a passionate Data Engineer looking to build resilient data architectures, optimize pipelines, and drive data-driven decision-making within a high-scale international ecosystem? At act digital, we are looking for a Data Engineer (French Speaker) with at least 4+ years of experience to join a strategic project in a hybrid setup based in Lisbon (Parque das Nações) (2 to 3 days on-site per week)!

Задачи:

• Design, implement, and maintain scalable, robust batch and real-time data pipelines (ETL/ELT).
• Collaborate on data modeling, data warehousing, and modern data lakehouse architectures to support advanced analytics and reporting.
• Implement data validation frameworks, monitoring, and automated data quality checks across the pipeline lifecycle.
• Tune SQL queries, monitor cluster workloads, and optimize data storage and processing performance.
• Work closely with cross-functional European teams (Data Analysts, Data Scientists, and Business Stakeholders) in an Agile delivery framework.

Требования:

• Minimum of 4+ years of hands-on experience in Data Engineering or ETL/ELT development.
• Strong proficiency in Python (or Scala / Java).
• Solid experience with cloud data platforms (e.g., Azure, AWS, GCP, Snowflake, Databricks, or BigQuery) and distributed systems (e.g., Spark or Hadoop).
• Hands-on experience with orchestration tools (e.g., Airflow, Prefect, ADF) and Git-based CI/CD workflows.
• French: Fluent / Professional working proficiency (B2/C1 minimum) to collaborate daily with francophone teams.
• English: Professional working proficiency.
• Будет плюсом: Experience within financial services, banking, or highly regulated enterprise environments; Knowledge of containerization (Docker, Kubernetes) and Infrastructure as Code (Terraform); Exposure to streaming architectures (Kafka, Event Hubs, Flink)

Условия:

Hybrid model (2 to 3 days per week on-site in Parque das Nações, Lisbon). Impactful projects within top-tier European organizations. Long-term stability within a certified Great Place to Work company. High-trust environment, continuous learning, and exposure to cutting-edge data stacks.