Senior Data Engineer

1 semana atrás

Lisboa, Portugal Remote Crew Tempo inteiro

About the Role We're looking for an experienced Senior Data Engineer to join our team and play a key role in designing, building, and maintaining robust data infrastructure that supports software used by thousands of companies and millions of users. In this role, you'll work closely with Data Scientists, Analysts, Architects, and Product teams to ensure data is accurate, secure, and available for analytics, reporting, and product development. You'll take ownership of data pipelines, data models, and integration processes that enable reliable, scalable data-driven solutions across the product. Location:Hybrid – 2x/week in office Contract Type:Full-time, employee Salary:€60k-70k/year Key Responsibilities Data Engineering & Delivery Design, develop, and maintain scalable data ingestion and ETL pipelines. Work with Architects and Product teams to define and agree core ingestion interfaces. Implement robust data transformations to support analytics and downstream use cases. Build and maintain data warehouses to support BI and API-based reporting. Partner with Data Scientists to productise analytical insights into structured datasets. Data Quality, Governance & Optimisation Develop and maintain data test frameworks to ensure accuracy, reliability, and integrity. Ensure data is catalogued correctly with appropriate security and sensitivity classifications. Optimise data models and pipelines for performance, scalability, and maintainability. Required Skills and Qualifications Proven experience as a Senior Data Engineer or in a similar role. Strong proficiency in Python, PySpark, and Databricks. Advanced SQL skills for data querying and transformation. Solid experience with ETL / data ingestion pipelines and data transformation processes. Strong understanding of data lake architectures and data warehousing. Experience developing data test and validation frameworks. Hands-on experience with Power BI for reporting and visualisation. Familiarity with cloud platforms such as AWS, Azure, or GCP and their data services.

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