Senior Platform Engineer – Data and Analytics (M/F/D)
- Compensation
- Not disclosed
- Location
- Lisbon, Portugal
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Full time
- Experience
- 6+ years
- Category
- Devops
- Posted
Skills
Must have
- You bring relevant technical education or equivalent practical experience that provides a strong foundation for enterprise platform engineering.
- You have 6+ years of relevant experience in platform engineering, DevOps or data engineering within enterprise cloud environments, with hands-on experience delivering solutions in real projects.
- You have strong practical expertise in Microsoft Azure and Azure Databricks, complemented by experience with technologies such as Terraform or Bicep, CI/CD, Unity Catalog, Delta Lake, Azure Data Facto
- Experience with Power BI platform administration or deployment automation is valuable.
- You combine hands-on engineering and pragmatic problem solving with an enthusiasm for automation and AI.
- You collaborate respectfully, share knowledge, adapt to different stakeholders and can make complex technical topics understandable to non-technical audiences.
- You are comfortable collaborating in an international environment with geographically distributed colleagues.
- Fluent in English - All Applicants are requested to deliver their CV in English language.
Full description
Senior Platform Engineer – Data and Analytics (F/M/D)
Ready to shape the next generation of Data & Analytics? Excited by Azure, Databricks and AI-powered automation? Want to turn complex technology into simple, scalable experiences? Join Essity and help us innovate for good.
About the Role
As a Senior Platform Engineer within our Data & Analytics environment, you will help build, automate, and evolve the engineering foundations that enable analytics and AI solutions to operate securely, reliably and at scale.
This is a hands-on platform engineering role where you will work across Microsoft Azure, Azure Databricks and Power BI.
You will strengthen DevOps and infrastructure-as-code capabilities while developing reusable platform services that make it easier for teams to build and consume data and analytics solutions.
You will also help shape how we use AI and intelligent automation to accelerate our move towards greater self-service analytics and AI powered decision intelligence.
What You Will Do
- Platform Automation: Build and maintain Azure and Databricks infrastructure using Terraform or Bicep, covering areas such as storage, networking, access controls, and Unity Catalog.
- Continuous Delivery: Develop and operate automated CI/CD pipelines for infrastructure, Databricks workloads and Power BI using Azure DevOps or GitHub Actions.
- Data Platform Engineering: Create reusable, metadata-driven ingestion and processing capabilities using Azure Data Factory, Databricks, Delta Lake, PySpark and SQL.
- Security & Governance: Strengthen platform security, access management, lineage, data quality, and governance to support trusted data and analytics.
- Reliability & Optimisation: Improve monitoring, performance, operational resilience, and cost efficiency across the platform.
- Engineering Standards: Establish good engineering practices, review technical solutions, mentor colleagues, and support teams in using the platform effectively.
- AI-First Engineering: Identify practical opportunities to use AI and intelligent automation to reduce manual work and continuously improve the engineering and user experience.
Who You Are
- You bring relevant technical education or equivalent practical experience that provides a strong foundation for enterprise platform engineering.
- You have 6+ years of relevant experience in platform engineering, DevOps or data engineering within enterprise cloud environments, with hands-on experience delivering solutions in real projects.
- You have strong practical expertise in Microsoft Azure and Azure Databricks, complemented by experience with technologies such as Terraform or Bicep, CI/CD, Unity Catalog, Delta Lake, Azure Data Factory, Python, SQL and PySpark.