Description
The key responsibilities of the Data Engineer will be structured around Database architecture, Ontology definition, Data Pipeline as well as Data Management, and will involve a significant amount of interactions with other AGT functions and the external parties.
- Systematic analysis the data contained within AGT data management systems, acquiring and building a deep knowledge of the data sets and processes thank to a consistent interaction with Subject-Matter Experts
- Translate the acquired knowledge into the appropriate staging and long-term data storage architecture.
- Iteratively develop, produce, expand, maintain and validate an overall Ontology based on the relevant data-sets available in the business.
- Define system to system data flow requirements, frequency, and validation
- Support the current and future Digital transformation project as SME in Data management
- Lead the work-streams to support the integration and standardisation of the data that feeds the Algorithm As A Service (AAAS) layer
- Populate the Knowledge Graph based on the Ontology and build the required data pipeline to ensure a consistent and automatic data upload
- Document and track the changes to the Ontology and Data Pipelines.
- Analytical support of ad-hoc request and data aspects of the Systems migration projects:
- Develop and design Cloud based data architectures as required by the current and future projects
- Lead the development of new data supply chains; devise methods of collection and systematisation of data
- Define rules for the monitoring of successful system to system data delivery and sync
- Define rules for monitoring the health of databases and knowledge graph
- Define rules and processes for automated data transfer and validation
- Generate database integrity and quality reports
Required
- Must demonstrate a practical experience in the field of data engineering: Demonstrable experience with Knowledge Graph, Ontology (Protégé + FluidOps), SQL, PostgreSQL is required. Knowledge of Cloud Platforms (AWS/Azure) is required. Knowledge of System-to-system integration tools (EG: SnapLogic) will be an advantage. Knowledge of a data driven programming language (Python or R) is a plus.
Qualifications, experience and skill set
- As a minimum: a Bachelors degree in Engineering, Reliability, Data Analysis, Mathematics or related science disciplines; results no lower than 2:1. The MSc qualification in the above topics will be preferred.
- Advanced knowledge of MS Excel and MS PowerPoint
- Knowledge and experience with statistical analysis of data.
- Experience in the repair and overhaul, fleet data management, and Oil & Gas sector are a plus.
- Familiarity with and experience in applying Lean methodology (eg Lean Six Sigma) will be an advantage.
- Genuine interest in data, information, emerging digital trends and their impact on the society and business development.
- Proactive, well-organised and result-oriented approach combined with an ability to communicate clearly and efficiently, both in writing and verbally.
- Ability to act independently, proactively and take ownership for the delivery.
- Customer-focused approach. Ability to build productive relationships with others and to build rapport with colleagues and internal customers to improve results
- Broad outlook combined with analytical mind-set: ability to make logical connections and understand the big picture quickly, as well as having a critical eye for data-driven improvements