Data Engineer - Energy Data Modelling

About Camlin

Camlin is a global technology leader that operates with the vision of bringing revolutionary products to life for a wide range of industries, including power and rail, and also has interests in a number of R&D projects in a variety of scientific sectors.

At Camlin we believe in high quality engineering and design, allowing us to develop market leading products and services. In short, we love creating value for our customers by solving difficult problems. As of now, Camlin operates in over 20 countries worldwide.🌐

The Role 

We are looking for a Data Engineer with strong expertise on data modelling and analytical data structures. 

Working closely with engineering and domain experts, you will understand electrical assets, their components, characteristics, relationships and operating conditions, translating this knowledge into structured and reusable data models. 

You will work with complex sensor, time-series, telemetry and operational data, developing data structures, transformations, calculations and engineering logic that accurately represent the underlying physical assets and their behaviour. 

The role goes beyond traditional data engineering focused primarily on data ingestion, pipelines and infrastructure. Its central focus is understanding the meaning of data and translating engineering knowledge into reliable data models and reusable analytical logic. 

We are open to considering candidates at both mid-level and senior level, with the position and responsibilities reflecting the successful candidate's experience. 

Technology Environment 

Our data environment includes Python, SQL, Apache Spark, PySpark and Databricks, alongside cloud-based data technologies. 

Experience with these platforms and technologies is advantageous. Strong underlying data modelling, programming and problem-solving skills are more important than familiarity with any specific technology. 

What Makes This Role Different 

This is not a traditional data engineering role focused primarily on infrastructure, data ingestion or pipeline development. 

The key challenge is understanding what the data represents and translating engineering knowledge into structured, reliable and reusable data models and analytical logic. 

You will work at the intersection of energy engineering, data modelling and analytics, helping build the data foundations behind solutions used to monitor and understand critical energy infrastructure. 

Key Responsibilities 

• Work with engineering and domain experts to understand electrical assets, their components, characteristics, relationships and operating conditions. 

• Design and develop structured data models representing electrical assets, hierarchies, components, measurements, events and their relationships. 

• Translate engineering knowledge and domain concepts into data structures, transformations, calculations and reusable engineering logic. 

• Develop data transformations and calculations using SQL and Python, working with sensor, time-series, telemetry and operational data. 

• Define and implement derived measurements, indicators and validation rules based on engineering concepts and principles. 

• Ensure data models accurately represent physical assets and their behaviour, establishing appropriate data quality, consistency and validation controls. 

• Take ownership of data modelling approaches, from understanding domain requirements and defining structures through to validation and documentation. 

• Collaborate with data scientists, engineering experts and software engineering teams to support the development and integration of analytical capabilities into customer-facing products. 

What We Are Looking For 

• A degree in Computer Science, Data Engineering, Engineering, Mathematics or a related technical discipline. 

• Experience in data engineering and data modeling. 

• Strong SQL skills and programming skills in Python. 

• Experience designing data models, structuring complex datasets and developing data transformations. 

• Ability to understand complex real-world systems, their components and relationships, and translate these into structured data models and reusable logic. 

• Experience working with interconnected datasets and defining relationships between different data entities. 

• Good understanding of data quality, validation, consistency and testing. 

• A structured approach to problem-solving, with attention to detail and maintainability. 

• Ability to work effectively with domain experts and collaborate across engineering, data and software teams. 

For senior-level candidates, we would additionally expect: 

• Experience designing data models for complex domains. 

• Ability to translate ambiguous engineering concepts into robust data structures and reusable logic. 

• Experience taking ownership of modelling decisions, technical implementation and data quality approaches. 

• Ability to establish consistent modelling practices and make sound technical decisions. 

Nice to have 

• Experience in the energy sector, particularly electrical networks, power systems or electrical infrastructure. 

• Knowledge of electrical assets such as transformers, switchgear, substations or overhead lines. 

• Experience modelling physical assets, asset hierarchies, components, measurements and relationships. 

• Experience working with sensor, time-series, telemetry or operational data. 

• Experience translating engineering concepts into calculations, derived measurements and reusable logic. 

• Familiarity with analytical modelling, feature engineering or data science workflows. 

• Experience developing data models and analytical capabilities that support software products. 

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.