Senior Data Platform Engineer

AdvanceWorks; Lisboa; Hybrid; EUR 70,000 - 95,000; Full time

Job summary

AdvanceWorks in Lisbon is seeking a Senior Data & AI Platform Engineer to support and evolve a cloud-based data platform. You will ensure environments, access, and integrations are healthy, automate CI/CD, and drive cost-optimisation alongside governance and observability efforts.

You will partner with Architecture, Data & AI Governance, Analytics and IT teams, contributing to reliability, security and scalable platform growth in a hybrid client setup.

Qualifications

• Proven senior experience as a Data & AI Platform Engineer in complex enterprise environments.
• Background as a Platform Engineer or SRE with data stacks, or DevOps moved to data platforms.
• Hands-on Azure expertise including ADLS Gen2 and Delta Lake.
• Experience with Azure Databricks and medallion architectures from a platform perspective.
• Familiarity with dbt and Apache Airflow/Astronomer as platform components.
• Experience building CI/CD pipelines and automation with Azure DevOps.
• Experience with Microsoft Fabric and Power BI.
• Knowledge of data governance tools such as Purview and Unity Catalog.
• Observability tools like Azure Monitor and Dynatrace.
• AI and MLOps platforms such as Azure ML, Microsoft Foundry and Databricks ML.
• Strong cloud, DevOps, DataOps, security and operations knowledge.
• Hands-on responsibility for cost management and FinOps practices.
• Ability to create standards, automation and technical documentation.
• Structured troubleshooting and root cause analysis skills.
• Clear communication with technical teams and stakeholders.
• Autonomy, accountability and a service-oriented mindset.
• Fluency in Portuguese and English, including technical documentation.
• Certifications (Azure, Databricks, Fabric/Power BI, DevOps, FinOps, ITIL/ITSM or security) are a plus.

Responsibilities

• Assess readiness of environments, workspaces, catalogues, access and integrations across the Data & AI platform.
• Define checklists and gates for onboarding, release and operational transition.
• Develop and maintain platform-specific CI/CD templates and automation using Azure DevOps.
• Define runbooks for deployment, rollback, hypercare and continuity.
• Implement and evolve monitoring with Azure Monitor and Dynatrace.
• Develop dashboards, alerts and reliability metrics for the platform.
• Follow up on incidents, identify root causes and drive preventive actions.
• Define tagging, naming and cost allocation standards.
• Build and maintain dashboards for cost monitoring and anomaly detection.
• Maintain and prioritise a backlog of cost optimisation opportunities.
• Provide technical support and enablement across the Data & AI ecosystem (Azure Databricks, dbt, Airflow/Astronomer, Fabric, Power BI).
• Support platform governance with Purview and Unity Catalog.
• Support AI/MLOps workloads on Azure ML, Foundry and Databricks ML.
• Produce technical documentation, runbooks and guides for platform users.
• Run knowledge transfer sessions for technical teams.
• Manage a continuous improvement backlog with KPI reporting.
• Collaborate with Architecture, Data & AI Governance, Analytics, Applied Intelligence, IT and Security teams.

Skills

Data Platform Engineer

Azure

Azure Databricks

CI/CD pipelines

Azure DevOps

Power BI

Observability

FinOps

Cost management

SRE mindset

Portuguese

English

Cost Allocation

Tools

Azure Databricks

dbt

Apache Airflow

Astronomer

Azure DevOps

Power BI

Delta Lake

ADLS Gen2

Purview

Unity Catalog

Azure Monitor

Dynatrace

Azure Machine Learning

Databricks ML

Job description

At AdvanceWorks, we learn together, grow together, and have fun together. And we do all this while creating great software solutions for clients across many industries and geographies.

We are constantly challenging ourselves and each other to use the latest technologies and the best methodologies and make sure we walk the talk.

About the project

You will join a project for a leading Portuguese group in mobility and transport infrastructure. The client’s Data, Analytics & AI department is strengthening its enterprise Data & AI ecosystem. The goal is to make sure platforms, tools, standards and processes keep pace with growing usage while staying reliable, secure, well governed and cost-efficient. The project combines hands-on technical work with platform enablement, including automation, observability, FinOps, documentation and support for technical teams.

The ecosystem is built on Microsoft Azure, with ADLS Gen2 and Delta Lake for storage and Azure Databricks running a medallion architecture. It also includes dbt, Apache Airflow / Astronomer, Azure DevOps, Microsoft Fabric and Power BI. Governance runs on Microsoft Purview and Unity Catalog, observability on Azure Monitor and Dynatrace, and AI and MLOps on Azure Machine Learning, Microsoft Foundry and Databricks ML.

This is a platform role, not a data product role. The work focuses on keeping the platform healthy, observable, optimised and ready to grow. Building pipelines, models or reports is not part of it. You will be part of the Engineering & Platforms team and work closely with Architecture, Data & AI Governance, Analytics, Applied Intelligence, IT and Security.

What will be your role

We are looking for a Senior Data & AI Platform Engineer to monitor, optimise, manage and evolve the platform that the client’s data and AI teams rely on every day. You will report to the Engineering & Platforms manager. Your job is to support the Data Engineering teams by looking after the platform they build on, not by building their pipelines. If Data Engineers are the ones driving, you will be the one maintaining the motorway.

Your work will sit where DataOps, FinOps and Site Reliability Engineering meet. You will check that environments, workspaces, catalogues, access and integrations are ready for use. You will also build and maintain CI/CD templates and automation, and define clear gates for onboarding, releases and operational handover. Monitoring, alerting and reliability metrics will be a core part of your day, along with following up on incidents and their root causes.

Cost management will be one of your main responsibilities. You will define tagging, naming and cost allocation standards, track spending and anomalies, and maintain a prioritised backlog of cost optimisation opportunities across the platform.

You will also be the go‑to person for technical support and enablement across the Data & AI ecosystem. This means producing documentation, runbooks and guides, running knowledge transfer sessions, and reporting regularly on activities and KPIs to drive continuous improvement.

Your responsibilities will include

Assessing the readiness of environments, workspaces, catalogues, access and integrations across the Data & AI platform.

Defining and maintaining checklists and gates for onboarding, release and operational transition.

Developing and maintaining platform-specific CI/CD templates and automation using Azure DevOps.

Defining runbooks for deployment, rollback, hypercare and continuity.

Implementing and evolving technical and functional monitoring of the platform with Azure Monitor and Dynatrace.

Developing dashboards, alerts and reliability metrics for the platform.

Following up on incidents, identifying root causes and driving preventive actions.

Defining standards for tagging, naming and cost allocation.

Building and maintaining dashboards for cost monitoring and anomaly detection.

Maintaining and prioritising a backlog of cost optimisation opportunities.

Providing technical support, troubleshooting and enablement across the Data & AI ecosystem, including Azure Databricks, dbt, Apache Airflow / Astronomer, Microsoft Fabric and Power BI.

Supporting platform governance in coordination with Microsoft Purview and Unity Catalog.

Supporting the platform components behind AI and MLOps workloads on Azure Machine Learning, Microsoft Foundry and Databricks ML.

Producing technical documentation, runbooks and guides for platform users.

Running knowledge transfer sessions for technical teams.

Managing and prioritising a continuous improvement backlog, with regular reporting on activities and KPIs.

Working closely with Architecture, Data & AI Governance, Analytics, Applied Intelligence, IT and Security teams.

What should you bring to the team?

Proven senior experience as a Data & AI Platform Engineer in complex enterprise environments.

Background as a Platform Engineer or Site Reliability Engineer working with data stacks, or as a DevOps Engineer who has moved into data platforms.

Hands‑on experience with Microsoft Azure, including ADLS Gen2 and Delta Lake.

Practical experience with Azure Databricks and medallion architectures from a platform perspective.

Familiarity with dbt and Apache Airflow / Astronomer as platform components.

Experience building CI/CD pipelines and automation with Azure DevOps.

Experience with Microsoft Fabric and Power BI.

Knowledge of data governance tools such as Microsoft Purview and Unity Catalog.

Experience with observability tools such as Azure Monitor and Dynatrace.

Experience with AI and MLOps platforms such as Azure Machine Learning, Microsoft Foundry and Databricks ML.

Good knowledge of cloud, DevOps, DataOps, observability, security and operations.

Real hands‑on responsibility for cost management and FinOps practices.

Ability to create standards, automation and technical documentation.

Structured troubleshooting and root cause analysis skills.

Ability to communicate clearly with technical teams and stakeholders.

Autonomy, accountability and a service‑oriented mindset.

Fluency in Portuguese and English, including for technical documentation.

Relevant certifications in Microsoft Azure, Databricks, Fabric/Power BI, DevOps, FinOps, ITIL/ITSM or security are a plus, as a complement to hands‑on experience.

Availability to work in a flexible hybrid model at the client’s headquarters in São Domingos de Rana, Lisbon.

What is in it for you

• An amazing informal culture of smart, hardworking, and friendly people who support and care about each other.
• A mentorship program from day one.
• The opportunity to work with real‑world operational data from tolling and Intelligent Transportation Systems.
• The opportunity to work on large-scale data and cloud projects using modern technologies.
• Formal training and certifications in data, cloud, and engineering excellence.
• Access to cutting‑edge tools and technologies.
• A dynamic company where your ideas matter more than job titles.
• Flexibility with responsibility.
• A Rubber Duck to help you debug those tricky data pipelines.

• If you have any questions, drop us a line at [e-mail]