Analytics Engineer, Emma Sleep
Mattresses & other sleep products
Open for applications
Mattresses & other sleep products
1001+ employees
Open for applications
1001+ employees
Company mission
To lead, disrupt, and reinvent the whole sleep industry.
Role
Who you are
- 3+ years in a data platform, data engineering, analytics engineering, DataOps
- Breadth over depth in a single tool - comfortable switching between topics, picking up unfamiliar problems, with a wide base of technical knowledge across the data stack
- Strong SQL and Python skills, with 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, etc), 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
- 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
What the job involves
- You'll join a cross-functional Data Platform Team serving Emma's broader Data and Tech organisation, with internal users spanning analysts, analytics engineers, data scientists and data engineers
- The team's mission is to make that work faster, safer, and more reliable - through observability, access control, engineering standards, code reviews, internal tooling, and AI adoption across the full pipeline from ingestion to BI tool consumption
- While the primary focus is analytics engineering tooling and process, you'll operate across the full stack, working closely with the Staff Analytics and Data Engineers to scope, build, and ship, while raising the bar for how the team builds
- The role rewards breadth and initiative over deep specialisation in one layer, requiring frequent context-switching and comfort with unfamiliar problems
- Reliability, Standards & Governance
- Own and improve monitoring, alerting, and observability across the data platform, so failures are caught early and pipeline/model health is visible to teams
- 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 our lakehouse, orchestration layer, data warehouse, and reporting systems, including code review culture
- Enablement & Internal Tooling
- Write clear guides, standards, and documentation that help colleagues across the Data domain work more efficiently and consistently, 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 our data infrastructure, in collaboration with the broader tech division
- Hands-On Pipeline & model development
- Enhance and build on our Redshift data warehouse using dbt and Paradime
- Orchestrate execution and dependencies between up/downstream pipelines (MWAA, Paradime), provisioning infrastructure via IaC (Pulumi, Terraform) so changes stay reproducible and version-controlled
- Contribute to our ingestion pipelines across three core patterns - simple ELT, containerised Python, and event-based - landing data reliably into our medallion lakehouse (S3, Glue, Iceberg)
Our take
Emma makes mattresses, bed frames and other sleep accessories that can be delivered right to your door. The company began in Frankfurt in 2013 at the beginning of a wave of similar companies emerging around Europe. It has since grown to operate in over 30 countries, and has become the world's most international direct to customer sleep brand.
The company owes this to its 'omnichannel strategy', selling both online and in store via retail partnerships, and it produces mattresses locally in each economy. With the launch of its retail-specific product assortment "Emma Select" and its pan-European partnership with the interior giant JYSK, Emma now collaborates with more than 200 different retail partners worldwide.
Emma's products continue to be awarded by reputable test institutes such as Stiftung Warentest in Germany and Which? (UK). It is aiming to strengthen both retail and marketplaces teams to anchor its expansion in Latin America as well as in the US. It will also be strengthening the product team and bringing yet more new sleep innovations to market.
Freddie
Company Specialist at Welcome to the Jungle
Insights
60% employee growth in 12 months
Company
Company HQ
Gutleutviertel, Frankfurt, HE
Leadership
Dennis Schmoltzi
(Co-Founder & Co-CEO)Dennis holds a Ph.D. in Finance fro Goethe University Frankfurt. Prior to founding Emma, he was an Engagement Manager at McKinsey & Company for nearly 7 years.
Manu Muller
(Co-Founder & Co-CEO)Alongside Emma, Manu is the CEO of Dunlopillo Deutschland. Previously, he co-founded Dormand where he served as the CEO for 6 years.
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