Pandora reaches millions of people across more than 100 countries — and behind every data-driven decision that shapes that reach is a data platform that needs to be fast, reliable, and trusted. We are transforming our Data & Analytics landscape with a modern cloud-based platform built on Databricks and Azure, and we are now building the central capabilies through the Data Enablement Team at the heart of it.

This team owns the capabilities that bring data from across the enterprise — including retail, e-commerce, supply chain, finance, and other source systems — into Pandora’s strategic data platform, and turns that raw data into a single governed definition of each core business entity — the Domain Layer that every downstream team builds on. As a Senior Data Engineer on this team, you will not just build pipelines; you will design the frameworks, standards, domain data models, and automation that make enterprise-scale data movement — and the business definitions built on top of it — reliable, repeatable, and easier for teams across the business to adopt.

This is a high-impact, high-ownership role for an engineer who takes pride in building things that last.

Design, build, and maintain scalable ingestion pipelines for batch, API, streaming, and event-driven integrations.

· Onboard new source systems onto Pandora’s strategic data platform, owning the end-to-end delivery.

· Develop reusable ingestion frameworks and platform capabilities that multiple teams can adopt.

· Design and build domain data models that turn raw ingested data into a single, governed definition of each core business entity (e.g. product, customer, order) shared across domains.

· Own delivery of domain data products — curated, trusted datasets that analytics, AI, and reporting teams can build on without re-deriving the same definitions.

· Partner with domain leads and business stakeholders to agree ownership, quality standards, and change management for shared business-entity definitions.

· Implement automated data quality controls to validate completeness, freshness, consistency, and accuracy of incoming data.

· Build monitoring, observability, and alerting capabilities to ensure reliable and transparent data movement.

· Design automated validation and testing frameworks to detect schema drift, breaking changes, and data anomalies before they impact downstream consumers.

· Implement resilient error handling, automated recovery mechanisms, and operational controls to minimise manual intervention.

· Contribute to metadata-driven and configuration-based ingestion solutions that simplify source onboarding at scale.

· Drive engineering excellence through CI/CD, Infrastructure as Code, automated testing, and DevOps practices.

· Act as a technical reference point for the team by contributing to architectural decisions, reviewing code, and raising engineering standards.

· Mentor and support less experienced engineers, sharing knowledge and fostering a culture of quality.

Partner with architects, platform engineers, source system owners, and product teams to shape scalable integration patterns across the organisation.

· Support the modernisation of legacy ingestion solutions towards Pandora’s target architecture.

· Provision and manage ingestion infrastructure as code, extending our Terraform-based automation to configure, version, and evolve platform resources reliably.

· Provide hands-on operational support for the wider data platform — including Unity Catalog configuration, access requests, and troubleshooting.

5+ years of experience as a Data Engineer, Platform Engineer, Integration Engineer, or Software Engineer working with enterprise data platforms.

· Strong hands-on experience with Python and SQL.

· Proven experience building and operating production-grade data pipelines at scale.

· Hands-on experience with Databricks, Apache Spark, and Delta Lake.

· Experience with data modelling and building governed, reusable data products (e.g. dimensional modelling, master data management, semantic layers).

· Experience partnering with business/domain stakeholders to define and maintain shared data definitions.

· Experience with Azure cloud services including Data Factory, Storage, Event Hub, and Key Vault.

· Experience integrating data through APIs, files, CDC, messaging platforms, or event-driven architectures.

· Strong software engineering fundamentals, including clean code, testability, modularity, and version control.

· Experience implementing CI/CD pipelines and DevOps methodologies.

· Hands-on experience provisioning and managing infrastructure as code (e.g. Terraform), and supporting the operational health of a broader data platform (e.g. Unity Catalog, access management).

· Experience building automated testing and validation frameworks.

· Experience implementing monitoring, observability, and alerting for data systems.

· Ability to contribute to architectural discussions and influence technical direction, not just execute on it.

· Experience mentoring peers or leading technical work within a team.

· Strong communication skills and the ability to engage confidently with both technical and non-technical stakeholders.

· Fluent English, written and spoken.

Nice to have

We do not expect all of these, but experience in any of the following would be a bonus:

· Apache Kafka

· Apache Airflow

· Terraform or other Infrastructure as Code tooling

· Unity Catalog

· Data contracts

· Change Data Capture (CDC)

· SAP integrations