Analytics Engineer, Data Platform

🕒 August 19

🌐 Germany, Portugal – Remote

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⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

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Logo of Emma – The Sleep Company

Emma – The Sleep Company

501 - 1000 employees

Founded 2013

🏥 Healthcare

🍽️ Food & Beverage

🧘 Wellness

Healthcare • Food & Beverage • Wellness

Emma – The Sleep Company is a company dedicated to enhancing people's sleep with innovative technologies and developments. Originally founded to improve sleep quality, Emma now invests significantly in research and development to produce scientifically-based products, such as award-winning mattresses in the UK. Emma also explores novel approaches to sleep enhancement, such as music albums for better rest and AI-powered sleep solutions. With a focus on e-commerce and technology, Emma – The Sleep Company is expanding globally, opening retail stores, and engaging in social initiatives such as Christmas toy donations and mental health awareness. Emma offers diverse career opportunities, encourages personal and professional growth, and supports a dynamic, international community of employees.

📋 Description

• Own and improve monitoring, alerting, and observability across the data platform • 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 • Support a code review culture • Write guides, standards, and documentation for colleagues across the Data domain • Drive alignment through knowledge-sharing forums • Build and maintain internal tooling, including AI-augmented workflows and observability and quality frameworks • Support AI adoption within data infrastructure in collaboration with the broader technology division • Enhance and build the Redshift data warehouse using dbt and Paradime • Orchestrate execution and dependencies between upstream and downstream pipelines using MWAA and Paradime • Provision infrastructure via Infrastructure as Code using Pulumi and Terraform • Contribute to ingestion pipelines using simple ELT, containerised Python, and event-based patterns • Land data reliably into the medallion lakehouse using S3, Glue, and Iceberg • Work across the full stack with Staff Analytics and Data Engineers to scope, build, and ship solutions • Raise engineering standards across the team

🎯 Requirements

• 3+ years in a data platform, data engineering, analytics engineering, DataOps, or closely related role in a production environment • Breadth across the data stack and comfort switching between topics and unfamiliar problems • Strong SQL and Python skills • Understanding of databases, including query execution, performance tuning, storage, access and permission models • Enough dbt experience to review others’ work and set standards • Working knowledge of AWS data technologies: Redshift, S3, IAM, Athena, and Glue, or equivalent • Experience with lakehouse architectures such as Apache Iceberg or Delta • Experience with pipeline orchestration such as Apache Airflow or equivalent • Experience with modern ingestion/ELT tooling such as Airbyte or Fivetran, or equivalent • Exposure to Infrastructure as Code, such as Pulumi or Terraform, or equivalent • Confidence navigating internal tooling and existing codebases • Strong communication and writing skills • Comfortable writing documentation, guides, and architecture decisions • Initiative and autonomy to drive work independently after onboarding • Fluent English, written and spoken • Based in Europe with workable timezone overlap • Role requires being based in Portugal or Germany

🏖️ Benefits

• Maturing Scale-Up: opportunity to build the next version of Emma while refining systems without losing agility • Empowerment to Impact: ownership, accountability, and development measurement • Growth & Learning Journey: trainings and coaching based on the 70/20/10 model • Emma-zing Community: collaborative community of smart, selective hires • Next Level Global: collaboration across cultures, perspectives, and time zones • Flexibility: remote work policy allowing great flexibility

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