Analytics Engineer, Data Platform

Stack

Responsibilities

• ▹Own and improve monitoring, alerting and observability across the data platform so failures are caught early and pipeline and model health is visible.
• ▹Contribute to architecture discussions: propose improvements, document trade-offs (ADRs, 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, including code review culture.
• ▹Write clear guides, standards and documentation for colleagues across the Data domain, driving alignment through knowledge-sharing forums.
• ▹Build and maintain internal tooling that removes friction for the teams you serve (e.g. AI-augmented workflows, extending observability and quality frameworks).
• ▹Support AI adoption within the data infrastructure in collaboration with the broader tech division.
• ▹Enhance and build on the Redshift data warehouse using dbt and Paradime.
• ▹Orchestrate execution and dependencies between up- and downstream pipelines (MWAA, Paradime), provisioning infrastructure via IaC (Pulumi, Terraform) so changes stay reproducible and version-controlled.
• ▹Contribute to ingestion pipelines across three core patterns (simple ELT, containerised Python, event-based), landing data reliably into the medallion lakehouse (S3, Glue, Iceberg).

Requirements

• ▹3+ years in a data platform, data engineering, analytics engineering, DataOps or closely related role in a production environment.
• ▹Breadth over depth in a single tool: comfortable switching between topics and picking up unfamiliar problems, with a wide base of technical knowledge across the data stack.
• ▹Strong SQL and Python skills, a real understanding of how databases work (query execution, performance tuning, storage, access and permission models), and enough dbt experience to review others' work and set standards.
• ▹Working knowledge of the AWS data stack (Redshift, S3, IAM, Athena, Glue) or equivalent, plus experience with lakehouse architectures (Apache Iceberg, Delta), pipeline orchestration (Apache Airflow or equivalent) and modern ingestion/ELT tooling (Airbyte, Fivetran or equivalent).
• ▹Exposure to Infrastructure as Code (Pulumi, Terraform or equivalent) and confidence navigating internal tooling and existing codebases.
• ▹Strong communication and writing: you can move between a stakeholder conversation about a problem and a technical discussion about how to solve it, and you are comfortable writing documentation, guides and architecture decisions.
• ▹Initiative and autonomy to drive work forward independently after onboarding, raising blockers early.
• ▹Fluent English, written and spoken; based in Europe with workable timezone overlap.

Soft skills

What we offer

• ▹Flexibility: the Technology team's remote work policy allows great flexibility (the role requires being based in Portugal or Germany)
• ▹Growth and learning: 70/20/10 model, trainings and coaching
• ▹International community: 60+ nationalities across 4 offices, global collaboration
• ▹Ownership and autonomy over your own area

About the company

Emma – The Sleep Company was founded in 2015 and has grown into the world's largest direct-to-consumer sleep brand, with a presence in over 20 markets and more than 35 stores across Europe.