Design, develop, and maintain scalable data pipelines using Databricks, PySpark, Python and SQL.
Build and optimise batch and near real-time data processing solutions on the Microsoft Azure ecosystem.
Develop and maintain Delta Lake-based data architectures.
Develop robust and scalable data products and modern data platform components supporting strategic business initiatives.
Contribute to CI/CD implementation and automation for data solutions.
Apply engineering best practices around source control, testing, deployment, and monitoring.
Support Infrastructure-as-Code and environment standardisation initiatives.
Ensure high standards of data quality, observability, monitoring, security, and operational reliability.
Collaborate with Product Managers, Architects, Data Engineers, and business stakeholders to deliver high-quality outcomes.
Participate in technical design discussions and contribute to solution architecture decisions.
Support platform governance, cost optimisation, technical documentation, and knowledge sharing initiatives.

5+ years of experience in Data Engineering
3+ years of hands-on experience with Databricks
Proven experience building and maintaining modern cloud data platforms
Experience working within Agile delivery environments
Proven ability to work effectively in distributed and international teams
Professional proficiency in English.
Strong hands-on expertise with: Databricks, PySpark, Delta Lake, Databricks SQL, Workflow orchestration, Performance tuning
Strong proficiency in: Python, SQL
Experience with: Microsoft Azure Data Platform services, Azure DevOps, Git-based development, CI/CD implementation, Data modelling, Data warehousing concepts
Good understanding of: Data Governance, Security and access management, Monitoring and observability.
Ability to design and deliver scalable, secure, and cost-efficient data solutions.

Senior Data Engineer, Databricks

Key skills