Job description:
Purpose of the role:
Group ICT are seeking a Data Engineer to work within a newly formed team. The candidate will use their knowledge of data analytics, language skills (SQL, PL/SQL, Python etc.), ETL, and data pipelines to support a newly established group wide data analytics function.Alongside the rest of the analytics team this position will work with all levels of the business and technical subject matter experts in the elicitation, analysis, modelling, documentation, reporting and management of data. The candidate will provide support to the data analytics team by implementing and consulting on the implementation of data management structures. The Data Engineer’s role has a strong focus on data ingress, data storage, data cataloguing, and data quality metrics.
Key Responsibilities:
The role includes, but will not be limited to the following:
Provide ad-Hoc Query Support: This activity involves helping customers and stakeholders with ad-hoc data calls. e.g. assisting stakeholders with one-off data query requirements to access feasibility of a larger project.
Recurring Data Quality Reports: This activity involves generation of reports and dashboards to all stakeholders.
Provide Data ingress and ETL Tools Support: Provide guidance and technical support to customers and stakeholders who want to use business intelligence tools provided (assisting with integration of the tools).
Assist Data Scientists and Business Analysts in converting business user stories into technical requirements.
Is responsible for supporting the development and maintenance of the ‘data warehouse’.
Works alongside 3rd party suppliers to deliver information solutions.
Ensures appropriate security and access control to the data.
Support user acceptance testing of new data warehouse features.
Help the client with root cause analysis of production data integrity issues. Creates queries that will resolve the integrity issues.
Works closely with end-users to gather report requirements and ensure proper testing/validation.
Supports end-users with report creation.
Interfaces with data providers to ensure data is submitted in the correct format.
Supporting the client through early problem detection, idea generation, and advising on "best practices”.
Can work to deadlines including, estimating, budgeting, and delivering data led projects.
Assist data analytics team in maintain data catalogue.
Qualifications Required:
Degree in mathematics, statistics, computer science, software engineering, data science or similar.
Experience & Skills Required:
Strong background in software engineering.
Must possess strong SQL or similar skills - at least 2 years’ experience.
Must possess strong Python or similar skills - at least 2 years’ experience.
Experience with unstructured/ semi-structured data is preferred.
Minimum 5 years overall experience.
Proficient with MS Office Tools (e.g., Outlook, Word, Excel, Project, PowerPoint, Visio).
Microsoft Data and Analytics Stack: Power BI, SQL Server, SQL Server Analysis Services (SSAS) and SSIS.
Administration level experience with the Microsoft Power Platform.
Software development methodologies.
Administration level experience with Azure with respect to Data and Analytics and basic understanding of ML and AI platforms preferable.
Exceptional oral and written communications skills.
English (required).
Spanish (highly regarded).
Behavioural Traits Required:
Ability to take little direction and achieve quality results independently.
Strong customer service focus.
Work well as part of a global, multi-cultural team.
The ability to multi-task, prioritize commitments and manage time effectively.
Attention to detail and follow-through.
Good working knowledge of Excel, financial modelling principles and development of algorithms to process large amounts of data.
Strong working knowledge of ERP solutions.
Experience in, or exposure to mining, manufacturing or similar heavy industry preferable.
A strong working knowledge of supply chain management i.e. the flow of goods in the supply chain, movement and storage of raw materials, work-in-process inventory, and finished goods from point of origin to point of consumption advantageous.
