Senior Data Analyst

As an analyst & lead smart controls, you are responsible for mapping out the needs of various use cases in the context of smart controls. You will make the functional translation of those needs to the developers, as well as follow up on their work and test the E2E process. You will take the lead in analyzing and following up on use cases, and will also work as the right hand of the product owner to e.g. also take the lead in certain scrum meetings to follow up on state of affairs, problems and the like, to supervise, to define necessary actions, etc. The smart controls are quite complex in nature. On the one hand, this involves understanding business processes in operations, asset management, R&D and Innovation in connection with wastewater processing, as well as understanding the necessary data flows, data needs, internal (aquafin) data both from internal applications and PLCs that send data to the cloud via MQTT as well as external data (precipitation/elec. prices/...) that are used to build smart controls. But also the necessary insight into error messages from smart controls, alarms to operations as well as general and functional follow-up of each of our smart controls. The intention is also that more and more work is being done towards machine learning & AI to also make use of predictions etc. There is a need for a structured approach, good analysis documentation and a lot of communication with the parties involved (Business Information Analysts per domain, Operating Technologies, source applications and stakeholders, product owners, data engineers, solution architect, business stakeholders...). Concrete Kennis & Capabilities
• Analytical thinking: A good analyst should be able to analyze and solve complex problems through logical thinking and reasoning.
• Analytical depth: sufficient experience with in-depth analysis is required, the data within Aquafin can be complex and widely distributed in systems, databases, or even manual data, being able to see the forest for the trees is important.
• Being able to link business processes to systems, data and ultimately to processes and to the functional building blocks behind smart management
• Proven insight into operational processes, being able to link business needs to processes and proactive insight into processes in order to be able to present the necessary challenges and questions to the business in order to critically evaluate their questions and proposals.
• Being able to design business processes and transform them into functional building blocks of controls as well as integration/communication agreements such as the layout of JSON files etc.
• Experience with data integration: the data analyst must have experience with integrating data from different sources and systems in order to achieve a useful result in terms of control.
• Good communication

skills:
the analyst/lead must be able to explain technical information to non-technical stakeholders in an understandable way, as well as be able to think along and empathize sufficiently with the various business areas and digital departments to bring the final solution to a successful conclusion in terms of the business needs and all stakeholders.
• Giving handover at the end of a use case to OT and operations.
• Knowledge of relevant laws and regulations: the analyst must be aware of the laws and regulations surrounding privacy, security and data safety.
• Experience with ER modeling: the data analyst should have experience in drawing up Entity Relation diagrams at different levels (such as conceptual, logical and physical).
• Knowledge and experience in all types of data modeling: Entity Relationship (ER) diagrams, star schemas, normalized vs dimensional, conceptual vs physical, ...
• Knowledge of Agile (SAFE) operation, sprint operation and possibly SCRUM master experience is a serious plus.
• Business process knowledge: The analyst must have knowledge of business processes to ensure that the solutions align with consistent and stable business processes.
• Knowledge of Azure, Parquet, medallion architecture, data warehousing, data lakes, Machine learning & AI, master data, databricks, mqtt/activemq, plc operation, is a plus
• Basic knowledge of SQL and Python is required
• Experience in the various aspects of data analysis: data source analysis, process analysis, data modeling, data reporting, data architecture, data quality, master data management, ...
• Experience in developing business and functional analyses and communicating them to the developers in a clear and structured way
• Testing: experience in developing and executing test scenarios

Skills:
bigdata,python,sql