Lead Data Engineer

Core details

• Company type: International Retail Group – In-house Data & Engineering

• Location: Cluj-Napoca, Romania

• Work model: Hybrid (2 days per week in the office)

• Engagement: Employment Contract, Permanent, Full-Time

• Role level: Senior / Lead level

• Experience level: 5+ Years

• Key Skills / Tech Stack: Python, SQL, PySpark, Apache Spark, Azure Databricks, dbt, Azure or GCP, CI/CD, data modelling, data quality, technical leadership

• Department: Engineering / Data

• Industry: Retail / Tech and digital

• About the client

Our client is a large international retail group with an in-house engineering organisation – technology is built internally, not outsourced. Teams own what they design and run, end to end, on platforms that serve the group’s markets and brands across Europe.

The Cluj engineering hub is part of a wider international ecosystem. The organisation is going through a period of change, and the data function is a central part of where it is heading.

• About the role

As Lead Data Engineer, you provide technical leadership across the development and evolution of cloud-based data platforms that support multiple retail brands at enterprise scale.

This is a hands-on leadership role. You remain close to the code: building, troubleshooting and optimising pipelines. At the same time you own technical design decisions, set engineering standards and mentor other Data Engineers across delivery squads.

You will work closely with Engineering Squad Leads, architects and cross-functional teams, with real influence over how the platform is architected and how data engineering is done.

• Responsibilities:

• Lead the technical design, development and optimisation of scalable data pipelines and distributed data processing solutions.

• Provide technical direction and guidance to Data Engineers across delivery squads.

• Own technical design decisions, ensuring solutions follow architecture principles and engineering standards.

• Stay actively involved in hands-on development, troubleshooting and pipeline optimisation.

• Establish and promote engineering best practices: code reviews, automated testing, data quality and maintainability.

• Mentor Data Engineers and help raise overall engineering standards.

• Work with architects, Squad Leads and stakeholders to translate business requirements into technical solutions.

• Drive improvements in development efficiency, CI/CD practices and the wider Data Engineering lifecycle.

• Support the reliability, performance and scalability of cloud-based data platforms.

• Contribute to technical discussions, knowledge sharing and the adoption of modern Data Engineering tools.

Qualifications:

• Strong hands-on Data Engineering background, with proven experience designing, building and maintaining large-scale distributed data processing systems.

• Advanced Python, SQL and PySpark, with strong knowledge of Apache Spark.

• Practical experience with Azure Databricks and dbt in production pipelines.

• Experience delivering cloud data solutions on Azure (preferred), AWS or GCP.

• Solid understanding of data architecture, data modelling, data quality, testing and storage best practices.

• Demonstrated technical leadership: architectural decisions, code reviews, mentoring and setting engineering standards.

• Experience with CI/CD, automated deployments and modern development practices.

• Ability to troubleshoot complex problems and optimise processing performance.

• Experience in Agile delivery environments and cross-functional teams.

• Strong communication skills and the ability to influence technical decisions.

• Excellent English, written and spoken.

About the offer

Our client offers a competitive package and room to grow:

• Competitive salary, annual performance bonus and employee referral bonus

• Private medical coverage through Regina Maria – Priority Plan, extendable to your spouse or children at no additional cost

• Life insurance through Metropolitan Life

• Eyeglasses vouchers and a co-funded 7Card fitness membership

• Access to LinkedIn Learning, LEO Learning and Bookster

• Meal vouchers, plus gift vouchers on several occasions throughout the year

• Additional days off when public holidays fall on weekends

• Paid leave for special life events

• Hybrid working model and a flexible schedule

• Modern, collaborative workspace with fresh fruit and premium coffee