What you will do:
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).
Who we're looking for:
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, 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 we offer:
Maturing Scale-Up: We’re part of the 13–20% of start-ups that transition to scale-up. This is a rare stage where we refine systems without losing agility. It’s where start-up energy meets scalable impact - and where people can build the next version of Emma.
Empowerment to Impact: Every Emmie owns part of our success with accountability. It’s about seeing it, owning it, doing it – something that is valued and measured in development.
Growth & Learning Journey: We live by the 70/20/10 model – with 70% on the job, 20% from others, 10% structured training. We invest in your growth with trainings and coaching to get you to the top of your game.
Emma-zing Community: We hire selectively which means working with smart, collaborative people who care deeply. It’s a community built by Emmies for Emmies.
Next Level Global: With 60+ nationalities across 4 offices, global collaboration is part of our values. You’ll work across cultures, perspectives, and time zones.
Flexibility: Our Technology team's remote work policy allows for great flexibility. (Please note that the role requires being based in Portugal or Germany)
