Principal Software Engineer

GFK - Growth from Knowledge.

For over 89 years, we have earned the trust of our clients around the world by solving critical questions in their decision-making process. We fuel their growth by providing a complete understanding of their consumers’ buying behavior, and the dynamics impacting their markets, brands and media trends.

In 2023, GfK combined with NIQ, bringing together two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights - delivered with advanced analytics through state-of-the-art platforms - GfK drives “Growth from Knowledge”.

It's an exciting time to be a builder. Constant technological advances are creating an exciting new world for those who understand the value of data. The mission of NIQ’s Media Division is to turn NIQ into the global leader that transforms how consumer brands plan, activate and measure their media activities.

By combining technology and our extensive data assets on consumer purchases, interests, lifestyles, and media, we allow advertisers to leverage outcomes to maximize their return on advertising spend.

Role Overview

We are looking for a Principal Software Engineer to provide technical leadership within our development teams, ensuring best practices, architectural coherence, and effective collaboration across projects. This role is ideal for a highly experienced engineer who can bridge the gap between data engineering, data science, and software engineering, helping teams build scalable, maintainable, and well-structured data solutions.

As a Principal Software Engineer, you will play a hands-on role in designing and implementing solutions while mentoring developers, influencing technical direction, and driving best practices in software and data engineering. This role includes line management responsibilities, ensuring the growth and development of team members. The role will be working within an Azure and Databricks environment, leveraging the power of cloud-native technologies and modern data platforms.

Key Responsibilities

Technical Leadership & Architecture

• Act as a technical architect, ensuring alignment between the work of multiple development teams in data engineering and data science.
• Design scalable, high-performance data processing solutions within Azure and Databricks, considering factors such as governance, security, and maintainability.
• Drive the adoption of best practices in software development, including CI/CD, testing strategies, and cloud-native architecture.
• Work closely with Product Owners and Engineering Managers to translate business needs into technical solutions.

Hands-on Development & Technical Excellence

• Lead by example through high-quality coding, code reviews, and proof-of-concept development.
• Solve complex engineering problems and contribute to critical design decisions.
• Ensure effective use of Azure services, Databricks, and data processing frameworks such as Apache Spark, Delta Lake, and Airflow.
• Develop and optimise data pipelines, data transformations, and ML workflows in a cloud environment.

Line Management & Team Development

• Provide line management to engineers, ensuring their professional growth and development.
• Conduct performance reviews, set development goals, and mentor team members to enhance their skills.
• Foster a collaborative and high-performing engineering culture, promoting knowledge sharing and continuous improvement.
• Support hiring, onboarding, and career development initiatives within the engineering team.

Collaboration & Cross-Team Coordination

• Act as the technical glue between data engineers, data scientists, and software developers, ensuring smooth integration of different components.
• Provide mentorship and guidance to developers, helping them level up their skills and technical understanding.
• Work with DevOps teams to improve deployment pipelines, observability, and infrastructure as code.
• Engage with stakeholders across the business, translating technical concepts into business-relevant insights.

Governance, Security & Data Best Practices

• Champion data governance, lineage, and security across the platform.
• Advocate for and implement scalable data architecture patterns, such as Data Mesh, Lakehouse, or event-driven pipelines.
• Ensure compliance with industry standards, internal policies, and regulatory requirements.

Requirements & Experience

• Strong software engineering background with experience in designing and building production-grade applications in Python, Scala, Java, or similar languages.
• Proven experience with Azure-based data platforms, specifically Databricks, Azure Data Lake, Azure Synapse, and Azure Functions.
• Expertise in Apache Spark and Delta Lake, with experience building large-scale distributed data pipelines.
• Experience with workflow orchestration tools like Apache Airflow.
• Cloud experience in Azure, including containerisation (Docker, Kubernetes) and infrastructure as code (Terraform, Bicep).
• Strong knowledge of modern software architecture, including microservices, event-driven systems, and distributed computing.
• Experience leading teams in an agile environment, with a strong understanding of CI/CD pipelines, automated testing, and DevOps practices.
• Excellent problem-solving and communication skills, with the ability to engage with both technical and non-technical stakeholders.
• Previous experience in data engineering, data science, or analytics-heavy environments is highly desirable.
• Proven line management experience, including mentoring, career development, and performance management of engineering teams.

Additional Information