Databricks Engineer

Adecco Recruitment; Lisboa; Híbrido; EUR 70 000 - 110 000; Tempo integral

Resumo da oferta

Adecco Recruitment is helping a world-renowned technology consulting client recruit a Databricks Engineer in Lisbon, with flexible hybrid work. The role focuses on modern data platforms for banking/finance and data products across global markets.

You will join an international team delivering end-to-end Databricks pipelines, applying best practices in lakehouse architectures, CI/CD, and governance. Strong PySpark, ADF, Airflow, and Azure DevOps experience are essential.

Qualificações

• Strong, demonstrable experience with Databricks as the primary engineering platform.
• Solid understanding of Medallion Architecture and modern lakehouse principles.
• Proficiency in PySpark and distributed processing frameworks.

Responsabilidades

• Build, optimize and maintain end-to-end Databricks pipelines, ensuring performance, reliability and scalability.
• Apply Medallion Architecture principles to design structured, maintainable and production-ready data layers.
• Develop distributed processing solutions with PySpark, aligned with best engineering practices.
• Design and orchestrate workflows using ADF and Airflow, improving automation and observability.
• Contribute to the evolution of Databricks Lakehouse standards, performance tuning and cluster optimization.
• Integrate CI/CD practices using Azure DevOps, with automated testing and version control.
• Collaborate closely with data scientists, architects and business stakeholders to operationalize data products and ensure alignment with financial-sector requirements.
• Support governance, security and documentation across the Databricks ecosystem.

Conhecimentos

Databricks

Medallion Architecture

PySpark

Azure Data Factory

Airflow

Azure DevOps

Git workflows

Agile

Ferramentas

Azure Data Factory

Airflow

Azure DevOps

Git

Descrição da oferta de emprego

Join a team where Databricks is at the heart of the engineering strategy and where your work powers largescale financial platforms used across global markets
Location Flexible Hybrid in Lisbon
Contract Fulltime, direct contract with a global technology consulting leader

Our client is a worldrenowned technology consulting company partnering with a major multinational in banking and financial services. This longterm program is part of a data and cloud modernization journey centred on Databricks, scalable architectures and highquality data products. You will join an international engineering environment dedicated to transforming complex data into reliable, governed and businesscritical assets.

Responsibilities

• Build, optimize and maintain end-to-end Databricks pipelines, ensuring performance, reliability and scalability.
• Apply Medallion Architecture principles to design structured, maintainable and productionready data layers.
• Develop distributed processing solutions with PySpark, aligned with best engineering practices.
• Design and orchestrate workflows using ADF and Airflow, improving automation and observability.
• Contribute to the evolution of Databricks Lakehouse standards, performance tuning and cluster optimization.
• Integrate CI/CD practices using Azure DevOps, with automated testing and version control.
• Collaborate closely with data scientists, architects and business stakeholders to operationalize data products and ensure alignment with financialsector requirements.
• Support governance, security and documentation across the Databricks ecosystem.

Required Skills

• Strong, demonstrable experience with Databricks as the primary engineering platform.
• Solid understanding of Medallion Architecture and modern lakehouse principles.
• Proficiency in PySpark and distributed processing frameworks.
• Experience with Azure Data Factory, Airflow and workflow orchestration.
• Familiarity with Azure DevOps CI/CD, Git workflows and automated deployments.
• Comfortable working in Agile, collaborative and multicultural environments.

Nice to Have

• Advanced experience with Azure DevOps for pipeline automation.
• Background in data testing or test framework development.
• Exposure to investment banking or financial services data landscapes.