Data Engineer Inside IR35 Remote workign - some travel to office required Main Purpose of JOB The Data Engineer will be responsible for the development of Data Pipelines and an Analytics Platform, maintain and extend our Data Model as we grow, and implement Data Governance principles. The role will collaborate with the team of data scientists and be critical to achieving additional value through innovative modelling. The Data Engineer will lead on establishing effective data provision and management. This role sits within Energy Portfolio Management, which provide Route to Market and Risk Management services to the Thermal, Renewable and Business Energy divisions. The Data Engineer will be part of the Advanced Analytics team which is focussed on building a modern data platform in Microsoft Azure and sophisticated analytical solutions using Machine Learning and AI.
The bulk of the data engineer's work will be in building, managing and optimizing data pipelines and data model used by our Data Scientists. They will also work closely with Data Management teams on governance and security as well as business stakeholders around projects and IT teams to deliver these data pipelines and models effectively into production. Key Accountabilities Architect, create, improve and operationalise integrated and reusable data pipelines Maintain a curated Data Model for use by Data Scientists for trusted and timely data Additionally, data engineers will also be expected to collaborate with data scientists, data analysts and other data consumers and work on the models and algorithms developed by them in order to optimize them for data quality, security and governance Guarantee compliance with data governance and SSE Security Standards
Measured on their ability to deliver data, analytics and data science results to business stakeholders Successfully transition from Discovery proof of concepts to production supported solutions Promote effective data management practices and better understanding of data and analytics.
The data engineer will also be tasked with working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal analytics and data science solutions.
Knowledge, Skills and Experience Business Knowledge Knowledge of the UK Wholesale Electricity markets would be advantageous
Excellent analytical skills
Excellent knowledge transfer and communication skills allowing you to engage with stakeholders at all levels.
Be a team player and enjoy collaborating with the Advanced Analytics team and wider business and IT teams
Essential Functional / Technical Skills Degree or equivalent in Mathematics, Physics, Computer Science, Engineering or related quantitative discipline. Extensive experience of developing using the Azure analytics components including:
Data Lake / Delta Lake Store,
Databricks Fully conversant with Agile and DevOps development methodology and concepts as applied to data driven analytics projects. Including CI/CD Coding, security testing best practice and standards.
Experience with designing, building, and operating analytics solutions using Azure cloud technologies
Data Management experience e.g. data profiling, large volume data handling
Experience in automated data driven testing
Experience in ETL Tooling Python (including Pandas, Numpy, PySpark, Jupyter, etc...), GIT
Personal Attributes / Competencies Intellectual curiosity, with excellent problem-solving and quantitative skills Motivated by innovative and creative approaches
Strategic approach aimed at building for success Excellent verbal, written, and interpersonal communication skills with the ability to present complex ideas to technical and non-technical audiences at all levels.
Strong people skills, collaborative team player, with a professional & positive attitude Ability and willingness to pick up new skills quickly Strong stakeholder management skills.
Comfortable discussing results with senior executives
Key Projects / Activities Managed (Identify impact, effort, cost, time invested) Developing and optimising data pipelines from Discovery projects to production in line with the Advanced Analytics Roadmap and targets.
Decision Making Authority Outline the most important decisions typically expected to be taken Responsible for selecting the right technical approaches to complex business and data problems
Outline the most important recommendations expected to be made for others to decide on Communicating optimal analytics solutions, optimised data models and algorithms for data science usage.
ersg are an equal opportunities employer; we are committed to promoting equality of opportunity for all job applicants. We do not discriminate against applicants on the basis of age, sex, race, disability, pregnancy, marital status, sexual orientation, gender reassignment or religious background; all decisions are based on merit