Data Engineer
Senior Data Engineer
Удалённоsenior
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About Camlin Group:
Camlin develops industrial technology and AI-driven systems used across the energy sector in more than 20 countries. We work on difficult real-world problems involving critical infrastructure, industrial sensor networks, and operational intelligence.
We are looking for a Senior AI & Data Engineer to help design and deliver AI and data products focused on predictive maintenance, anomaly detection, asset monitoring, and energy forecasting. This is a hybrid working permanent role (3 days on-site, 2 days work from home).
This is a highly hands-on engineering role for someone who enjoys solving difficult AI and 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 AI and data projects.
What you'll work on:
You’ll help build AI and 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
- Production ML systems operating on large-scale multimodal datasets
The work involves difficult real-world constraints:
- Noisy and incomplete sensor data
- Sparse labels and uncertain signals
- Large-scale time-series datasets
- Scaling AI systems into real world solutions
- Translating unclear requirements into practical delivery plans
What you'll do:
- Design and build AI and data systems from early concept through model creation
- Work closely with data scientists, product managers, and domain experts to shape technical solutions
- 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 and ML workflows using modern cloud-native tooling
- Influence technical direction, architecture decisions, and product roadmap discussions
- Evaluate trade-offs between model accuracy, reliability, complexity, latency, and operational cost
- Help drive measurable outcomes with clear KPIs and visible business impact
- Improve engineering quality, maintainability, and operational reliability across the stack
Our current tech stack includes:
- Python
- Apache Spark
- Databricks
- MLflow
- Modern cloud-based data platforms
- Large-scale industrial and time-series datasets
What we are looking for:
- Experience building real-world AI, ML, or data products
- Experience working across data engineering and ML 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 probably
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
This role starts as a senior individual contributor position with strong technical influence. Over time, the expectation is that you will increasingly shape technical plans, mentor engineers, and take ownership of larger AI and data initiatives across the organization.
Success in this role means:
- Delivering AI systems that create measurable operational value
- Reducing uncertainty and technical risk early
- Helping teams make better engineering and product decisions
- Building trust across engineering, product, and domain teams
- Driving predictable delivery in complex industrial environments
Why this role stands out:
- Work on unusual industrial and energy datasets
- Build AI capabilities with visible business impact
- Solve technically challenging real-world problems
- Operate with meaningful ownership and influence
- Help shape the future direction of AI systems in critical infrastructure
Our Values
- We work together
- We believe in people
- We won’t accept the ‘way it’s always been done’
- We listen to learn
- We’re trying to do the right thing
Benefits:
- 25 Days of Annual Leave
- FitPass membership
- Private Health Insurance
- Internal Reward & Recognition Tool Kudos
EQUAL EMPLOYMENT OPPORTUNITY STATEMENT
Individuals seeking employment at Camlin are considered without regards to race, colour, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, gender identity, or sexual orientation.
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