Senior Data Engineer
Quick Summary
energy domain knowledge Python as our main programming language Databricks Spark for data processing Databricks/dbt/SQL for data modelling and analytics Streamlit for data applications and
Acting as the flexibility team’s first full-time data engineer, establish the team’s data capability, lead the team’s data engineering technical direction and represent the team to the cross-team data community
Upskill data-literate backend engineers, act as the team's data expert and as a multiplier on other engineers' impact
Establish greenfield data engineering systems in a newly established AWS environment
Provide a foundational layer of high quality data processing and warehousing that will enable future projects for both our team and others
Maintain and develop critical data applications - scoping and implementing architectural improvements for long-term global scalability, robustness and operational efficiency
Interface with the established data warehouse, built on Databricks
Take ownership of data platform improvements that enhance the capabilities for all teams and drive trust in the stability of the system
Strong aptitude with SQL, Python and AWS data stack essential;
Experience building efficient, scalable databases and APIs (e.g. Django, FastAPI) a huge plus;
Experience in Kubernetes, Docker, Spark and related monitoring tools (e.g. DataDog, Grafana, Prometheus) for DataOps a huge plus;
Experience with Airflow a huge plus;
Experience with dbt for pipeline modelling also beneficial;
Skilled at shaping needs into a solid set of requirements and designing scalable solutions to meet them;
Able to quickly understand new domain areas and visualise data effectively;
Team player excited at the idea of ownership across lots of different projects and tools;
Drives knowledge sharing and documentation for a more effective platform;
Desirable: energy domain knowledge
Python as our main programming language
Databricks Spark for data processing
Databricks/dbt/SQL for data modelling and analytics
Streamlit for data applications and visualisations
Airflow for job scheduling and tracking
CircleCI for continuous deployment
Parquet and Delta file formats on S3 for data lake storage
Terraform for our infrastructure definition
Kubernetes for data services and task orchestration
Datadog/Grafana/Prometheus for platform monitoring
Django for custom databases and frameworks
Postgres / Aurora for our relational databases
Notion for documentation
Location & Eligibility
Listing Details
- Posted
- September 2, 2026
- First seen
- September 2, 2026
- Last seen
- September 3, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 62%
- Scored at
- September 2, 2026
Signal breakdown
Repos belonging to (mainly) Kraken Customer and Field
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