What you'll work on:
You’ll help build data products used in energy environments, including:
- Predictive maintenance systems for critical infrastructure
- Anomaly detection on sensor data
- Asset monitoring and operational intelligence platforms
- Energy forecasting and time-series modelling systems
The work involves complex real-world constraints:
- Noisy and incomplete sensor data
- Sparse labels and uncertain signals
- Large-scale time-series datasets
- Scaling systems into real world solutions
- Translating unclear requirements into practical delivery plans
What you'll do:
- Design and build end-to-end data-driven products that are part of our SaaS offering
- Work closely with data scientists, product managers, and domain experts to shape technical solutions
- Work alongside frontend, backend, and data engineers to deliver customer-facing features, supporting the development of backend APIs and frontend visualizations
- Turn ambiguous business and operational problems into structured engineering plans
- Prototype and validate ideas quickly to reduce technical and product risk early
- Build scalable data pipelines using modern cloud-native tooling
- Influence technical direction, architecture decisions, and product roadmap discussions
- Improve engineering quality, maintainability, and operational reliability across the stack
Our current tech stack includes:
- Python
- Apache Spark
- Databricks
- PostgreSQL
- Modern cloud-based data platforms (AWS)
- C#/.NET
What we are looking for:
Mandatory knowledge of
- PySpark/Databricks
- CI/CD pipelines
- Knowledge of C#/.NET is a plus
- Experience building real-world data products
- Experience working across data engineering systems, not just isolated pipelines
- Comfortable operating in environments with uncertainty and evolving requirements
- Pragmatic engineering mindset focused on outcomes and business impact
- Ability to make and communicate trade-offs clearly
- Systems thinker who can connect architecture, product goals, and operational constraints
- Strong communication skills with both technical and non-technical stakeholders
- Collaborative approach with a willingness to challenge assumptions constructively
This role is not a good fit if you:
- Primarily identify as a pipeline-only or ETL-focused engineer
- Prefer fully specified requirements before starting work
- Want narrowly scoped responsibilities without product or technical ownership
Our Values
- We work together
- We believe in people
- We won’t accept the ‘way it has always been done’
- We listen to learn
- We’re trying to do the right thing
Equal Employment Opportunity Statement
Individuals seeking employment at Camlin are considered without regards to race, colour, religion, national origin, age, sex, marital states, ancestry, physical or mental disability, gender identity or sexual orientation.
About Camlin
Camlin develops industrial technology and AI-driven systems used across the energy sector in more than 20 countries. We work on complex real-world problems involving critical infrastructure, industrial sensor networks, and operational intelligence.
We are looking for a Senior Data Engineer to help design and deliver data products focused on predictive maintenance, anomaly detection, asset monitoring, and energy forecasting.
This is a highly hands-on engineering role for someone who enjoys solving difficult data problems in real operational environments. You’ll work closely with domain experts, product stakeholders, and engineers to turn data into reliable systems that create measurable business impact.
We are looking for someone who can combine strong technical execution with the ability to bring structure, clarity, and momentum to complex engineering initiatives. You’ll play an important role in shaping technical plans and driving delivery across a suite of data-driven products.