Analytics Engineer, Data Platform

About This Opportunity

We are representing a fast-scaling direct-to-consumer brand with a presence across multiple European markets. Our client is building out their data infrastructure to support a growing international organization, and we're seeking an Analytics Engineer to join their Data Platform Team in Frankfurt.

This is a cross-functional role serving analysts, analytics engineers, data scientists, and data engineers. You'll work on the full stack—from ingestion pipelines to BI consumption—focusing on making data work faster, safer, and more reliable through observability, tooling, standards, and AI adoption. The role rewards breadth and initiative over deep specialization, requiring comfort with context-switching and tackling unfamiliar problems.

Responsibilities

• Own and improve monitoring, alerting, and observability across the data platform to ensure pipeline and model health is visible and failures are caught early
• Contribute to architecture discussions, propose improvements, document trade-offs through ADRs and RFCs, and help decide what to build, refactor, or retire
• Set, document, and enforce engineering standards and best practices across the lakehouse, orchestration layer, data warehouse, and reporting systems
• Build and maintain internal tooling that removes friction for data teams, including AI-augmented workflows and quality frameworks
• Write clear guides, standards, and documentation to help colleagues work more efficiently and consistently
• Support AI adoption within the data infrastructure in collaboration with the broader technology division
• Enhance and build on the Redshift data warehouse using dbt and Paradime
• Orchestrate execution and dependencies between pipelines using MWAA and Paradime
• Provision infrastructure via IaC tools like Pulumi and Terraform to keep changes reproducible and version-controlled
• Contribute to ingestion pipelines landing data into a medallion lakehouse architecture using S3, Glue, and Iceberg

What We're Looking For

• 3+ years in data platform, data engineering, analytics engineering, DataOps, or a closely related production role
• Breadth over depth: comfortable switching between topics and picking up unfamiliar problems with a wide technical foundation across the data stack
• Strong SQL and Python skills with real understanding of database internals including query execution, performance tuning, storage, and access models
• Solid dbt experience sufficient to review others' work and set standards
• Working knowledge of AWS data services (Redshift, S3, IAM, Athena, Glue) or equivalent cloud platforms
• Experience with lakehouse architectures such as Apache Iceberg or Delta
• Familiarity with pipeline orchestration tools like Apache Airflow or equivalent
• Experience with modern ingestion/ELT tooling such as Airbyte or Fivetran
• Exposure to Infrastructure as Code using Pulumi, Terraform, or similar tools
• Strong communication and writing skills; ability to move between stakeholder conversations and technical implementation discussions
• Comfortable writing documentation, guides, and architecture decision records
• Initiative and autonomy to drive work forward independently, raising blockers early
• Fluent English, written and spoken
• Based in Europe with workable timezone overlap (role requires location in Germany or Portugal)

How We Work With You

When you apply through Get A Job.ai, our talent team will review your profile and conduct an initial screening. If there's a strong match, we'll submit your application to our client on your behalf. Please do not contact the client directly—all communication and coordination will flow through our recruiting team to ensure the best experience for you and the hiring organization.

Pay

Compensation details will be discussed during the screening process based on your experience and the client's budget for this role.

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