Principal Platform Engineer (m/f/d)

Shopware is a leading ecommerce system that enables companies worldwide to scale quickly and efficiently in digital commerce. As a trendsetting open source solution, Shopware is already used by some of the largest European brands, retailers and manufacturers in the B2C and B2B industries.

We're hiring a Principal Platform Engineer (m/f/d) to build and run the Data Platform: the ingestion, storage, and pipeline runtimes that every data pipeline at Shopware runs on. You own its architecture and reliability, from CDC ingestion through a three-tier lake to the orchestration substrate underneath it.

What you build is what lets Service teams and senior leadership understand our customers and our product. It's also the infrastructure that data governance and compliance depend on to be enforceable at all.

You'll partner with Data & AI, who builds the pipelines on top of what you run. As a member of the Service Enablement Team, you will keep the same golden-path philosophy and maturity bar applied to the Data Platform as on the rest of the Service Platform. This is a senior individual-contributor role, not a people-management one, but you must be comfortable reaching out to many stakeholders, peers, and partners.

• Ingestion: CDC ingestion (DMS/Lambda) into raw S3, and the raw schema and contracts, which today spans 13 domains and roughly 180 schemas across three tiers, with 11 CDC sources already live in production and more onboarding.

• Storage & orchestration: the Terraform-provisioned orchestration substrate (Step Functions/EventBridge/Glue) across all three lake tiers (raw/curated/aggregated) and its CDC Terraform modules.

• Data cataloguing infrastructure: hosting and operating OpenMetadata is part of the offering: you run the catalog infrastructure, the same operator/consumer split as the lake tiers, and Data & AI builds dataset descriptions, glossary, and stewardship content on top of it.

• Tooling infrastructure: hosting for Superset, the tool teams use to query and visualize data.

• The pipeline boundary: clear code boundaries, a merge-blocking contract gate, and an incident-routing rule: you get pinged or paged for infrastructure, not for pipeline logic.

• Reliability: observability and operational-excellence practices (Datadog, incident response, SLOs/SLIs) for the Data Platform, and its on-call rotation, compensated at parity with every other team's rotation from day one.

• Governance and compliance mechanics: the policy itself (classification standards, retention rules, GDPR/privacy request handling) is owned outside both SET and Data & AI, by Legal/Compliance or a DPO-adjacent function. You don't set that policy, but you implement the architecture it depends on: retention windows, access controls, classification metadata, and deletion-request propagation.

• Cross-Platform consistency: working with the Infrastructure Principal Platform Engineer so the Data Platform follows the same self-serve philosophy and maturity bar as the rest of the Platform.

This is what you’ll bring to the table:

• Deep, hands-on AWS experience (Glue, Athena, Step Functions, EventBridge, Lake Formation, S3) alongside strong Terraform experience authoring and evolving shared modules.

• Working knowledge of CDC pipelines and Iceberg-based lakehouse tiering (raw/curated/aggregated). That's the format actually in production today, not a hedge.

• Familiarity with Kafka-based event streaming (MSK, Glue Schema Registry) for application-level events, landing alongside CDC.

• Comfort operating a platform other teams depend on: incident response, SLOs, and the judgment to route a bespoke request into a backlog rather than building it ad hoc.

• Strong cross-team communication: you'll partner directly with Data & AI to keep the infrastructure/pipeline-logic boundary clear as it evolves, and with the Infrastructure Principal Platform Engineer on cross-cutting standards, without either relationship being a reporting line.

• Acute understanding of what makes a data-driven culture actually stick: leaders acting on metrics, data literacy org-wide, infrastructure accessible to all target users, data as a shared asset.

• Comfortable managing up: surfacing trade-offs and risks to leadership proactively rather than waiting to be asked.

• Clear, direct written communication; comfortable proposing and defending a technical position to both engineering peers and non-technical stakeholders.

Nice to have

• Familiarity with dbt (dbt-athena) or Spark/pySpark, enough to have a productive conversation about where the infrastructure/pipeline-logic boundary should sit as it evolves.

• Experience building an on-call rotation for a team that didn't previously have one.

• Prior experience partnering with legal/compliance stakeholders directly. Translating a retention or classification requirement into an actual infrastructure decision, not just being aware one exists.

This is what we offer you:

• Company Culture: Open culture with flat hierarchies, where individual initiative is encouraged.

• Employment Contracts: Permanent positions that offer long-term security.

• Flexibility: Flexible working hours and options for mobile work and full-remote contracts.

• Equipment: Freedom to choose your preferred work hardware.

• Onboarding: Well-structured onboarding with support from a personal "buddy."

• Work Environment: An inspiring environment with dedicated colleagues and a dynamic community.

• Development Opportunities: Diverse opportunities for personal growth and development.

• Additional Benefits: Attractive perks such as company pension plans, health programs, and regular team events.

... and much more!

You can get a detailed insight on our career page.

Your personal contact for this position is Yanina Schröer and is happy to answer any questions you may have!

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