Data Lakehouse Lead

The Data Lakehouse Lead is responsible for the technical implementation, evolution and outcomes of the organization's shared Data Lakehouse. The Lakehouse provides the trusted, structured and reusable data foundation required to develop and evolve the analytical capabilities at the core of Camlin's energy monitoring and analytics products.

This is a technical leadership role combining Data Engineering, data modelling, planning and stakeholder alignment.

About Camlin

• This streamlines and automates the process of acknowledging and appreciating employees and helps contribute to our positive workplace culture.
• 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

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. 🌐

Responsibilities

• It brings together complex sensor, time-series, telemetry and operational data, making it accessible and meaningful for analytical development, as well as supporting AI and other data-driven use cases.
• The role combines strong Data Engineering and data architecture expertise with technical leadership, planning and stakeholder alignment.
• It works closely with Analytics teams, engineering and domain experts, and technical and business stakeholders to understand needs, define priorities and drive the evolution of the Lakehouse.
• The role ensures that Camlin's shared data foundation is technically sound, coherent and fit for purpose, enabling Analytics teams and Data Scientists to develop and scale the analytical intelligence underpinning the organization's energy monitoring and analytics products.
• Define and evolve the technical architecture, design principles and data modelling approach for the Data Lakehouse.
• Establish meaningful and reusable conceptual, logical and physical data models that accurately represent the business and engineering domains and support analytical use cases.
• Lead the implementation of shared datasets and data products, ensuring consistency in business definitions and data structures.
• Ensure data models appropriately represent underlying entities, relationships and behaviours, including assets, measurements and operating conditions.
• Define standards and patterns for data ingestion, modelling, transformation, storage and consumption.
• Translate business and analytical needs into clear data objectives and engineering priorities.
• Lead planning of the Data Lakehouse roadmap, developing proposals and recommendations that balance priorities, capacity, dependencies and technical needs.
• Align objectives, scope and expected outcomes with Analytics teams and other stakeholders, contributing to roadmap prioritisation and decision-making.
• Ensure shared data products meet agreed standards for quality, reliability, documentation, lineage and usability.

Requirements

• Data Engineers and provide technical leadership on complex engineering and architectural challenges.
• Strong professional experience in Data Engineering and modern data platforms.
• Ability to understand complex business domains and translate business concepts into meaningful and reusable data models.
• Experience working with complex data domains and datasets, ideally including sensor measurements, time-series, telemetry or operational data.
• Strong understanding of data architecture, modelling and modern Lakehouse patterns.
• Understanding of data quality, metadata, lineage and data governance.
• Strong planning and prioritisation skills, with the ability to lead planning activities, develop recommendations and align stakeholders around clear objectives and deliverables.
• A results-oriented approach, focused on measurable outcomes rather than technical activity alone.
• Ability to provide technical leadership to Data Engineers and collaborate effectively with Analytics, AI and Data Science teams.
• Strong architectural, problem-solving and communication skills, with pragmatic decision-making and the ability to engage both technical and non-technical stakeholders.
• Nice to have Experience in the energy sector, industrial monitoring or engineering-related data environments.
• Familiarity with electrical infrastructure, asset monitoring or operational technology data.
• Experience working with sensor measurements, time-series data and telemetry.
• Experience building data foundations that support analytical development and the integration of analytical capabilities into software products.
• Environment Our data environment includes Python, SQL, Apache Spark, PySpark and Databricks, alongside cloud-based data technologies.
• Strong underlying Data Engineering, data modelling, and problem-solving skills are more important than familiarity with any specific technology.

Preferred

• Experience with these technologies is advantageous.

Benefits

• Daily food vouchers: for days worked in person in the premises.
• We offer financial assistance for your training and development, based on company discretion.
• We also have an internal training platform to support your professional and personal development.
• Stay fit with our discounted gym membership program.
• We prioritise your well-being through our wellness initiatives.

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.