Engineering Lead - Analytics Platform
Team: Data
Location: United Kingdom, London (GB)
Commitment: Full-time
Workplace Type: hybrid
What You'll Do...
- Build & maintain awesome tooling for data transformation, visualisation, and AI – combining the best of open source, SaaS, and in-house tech
- Establish a data architecture that enables easy discovery, cross-team working, and global reuse of data products – for technical and non-technical users
- Partner with data teams to scope & prioritise opportunities, and deliver solutions that have measurable business impact
- Foster a growing community of Analytics Engineers with training, documentation and collaboration
- Manage a multi-skilled team of 3 - 5 engineers, supporting their development and happiness
What You'll Have...
- Passion for being at the cutting edge of analytics engineering – dbt is just the start!
- Breadth and depth of experience in the Analytics development lifecycle
- Extensive knowledge of Python and Git, with solid software engineering foundations e.g. testing, CI/CD, and observability
- Ability to work with a range of technical & non-technical stakeholders, managing competing needs and prioritising value
- Autonomy and pragmatism, as projects will be varied and self-driven
- Leading small teams
- Looking after BI platforms like Lightdash, Looker, Omni or Metabase
- Managing software vendors
Our Data Platform Stack...
- We employ software engineering best practices to design, test, and deploy our data platform and services using the below technologies:
- Python, SQL and dbt
- Lightdash as our BI tool & semantic layer
- Streamlit for interactive data applications
- Databricks data platform with Delta Lake
- Airflow for orchestration
- Kubernetes for application deployment
- CI/CD with GitHub and CircleCI
- Infrastructure on AWS, deployed with Terraform / Spacelift
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