About this role
What you can expect from usWe’re a high‑energy cloud- and data engineering team looking for like-minded, motivated tech builders. We are driven by ownership and business outcomes.
As the analytics unit within a global management consultancy, we turn data-driven strategies into production systems. Our clients are DAX and Fortune Global 500 leaders who trust us for our expertise across data platforms, big data and cloud engineering.
You’ll join an international environment with agile squads and a boutique spirit with room to experiment and grow, paired with above‑market compensation and an attractive benefits package.
What you’ll do as part of our cloud- and data engineering team:
Take ownership for projects end to end: From scoping to stakeholder alignment and the delivery of measurable outcomes
Design data architectures for batch and streaming workloads, both at small and big data scales
Provision and manage the underlying cloud infrastructure to support those architectures on providers such as AWS, Azure or GCP
Building Python ETL/ELT pipelines, orchestrated with Airflow, Dagster, or Prefect.
Work with data lake technologies and optimize (OLAP) data ware-/lakehouses
Model and store data across SQL and NoSQL databases, as well as optimizing performance and costs
Create web APIs with popular Python frameworks (e.g.,FastAPI and Flask) and describe them using standards likeOpenAPI/Swagger
Automate deployments using Infrastructure-as-Code and container technologies such as Docker, <sp
Responsibilities
- Take ownership for projects end to end: From scoping to stakeholder alignment and the delivery of measurable outcomes
- Design data architectures for batch and streaming workloads, both at small and big data scales
- Provision and manage the underlying cloud infrastructure to support those architectures on providers such as AWS, Azure or GCP
- Building Python ETL/ELT pipelines, orchestrated with Airflow, Dagster, or Prefect.
Requirements
- Work with data lake technologies and optimize (OLAP) data ware-/lakehouses
- Model and store data across SQL and NoSQL databases, as well as optimizing performance and costs
- Create web APIs with popular Python frameworks (e.g.,FastAPI and Flask) and describe them using standards likeOpenAPI/Swagger
- Automate deployments using Infrastructure-as-Code and container technologies such as Docker, <sp