Be part of a team tasked with producing high quality, innovative solutions to enhance our core business systems and create significant intellectual property that will differentiate us in our sector and markets. You'll be instrumental in helping establish a leading data and analytics strategy and associated processes, and steer the team in the direction of self-service and delivery life cycle automation for reporting and analysis capabilities.
This is a role for a sector specialist who has experience working as Business Intelligence Analyst or Engineer in a fast-paced environment and for someone who is friendly, approachable and proactive in bringing new ideas to the table.
* Analyse reporting requirements to design and deliver solutions that meet our goals and objectives as standalone changes or as part of a broader programme of work.
* Evaluate business processes and identify opportunities to simplify, standardise and optimise cross-firm processes using business intelligence and data tools.
* Identify data gaps or data acquisition needs and ensure they are clearly documented and presented to the Data Engineering team for development.
* Advise on data solutions designs so that the business intelligence platform and semantic model is optimised for performance and accuracy.
* Prototype, demonstrate and document solutions by working hands-on with stakeholders.
* Define and implement an agile delivery method, test automation and QA processes for our reporting and analytic solutions.
* Manage 3rd party/external development teams acting as a team lead/scrum master where necessary.
* Work with our Head of Service Management and DevOps specialist to ensure that delivery aligns to our cloud and change management processes.
* Perform unit and system acceptance testing against (non) functional requirements.
* Contribute to the definition and maintenance of our target state solution architecture, development frameworks and delivery methods.
* Establish operational support processes for our reporting solutions, set the priorities for the operational support teams and champion Service and Support considerations and service transition activity in all development activity.
* Detailed working knowledge of one or more market leading business intelligence platforms or tools (MicroStrategy, Qliksense, IBM Cognos, PowerBI, Tableau).
* Expert knowledge of business intelligence concepts, data visualisation and analytic methods.
* Data Modelling: The ability to design and implement effective database models that are optimised for reporting and analysis.
* Extensive track record of business analysis and business process optimisation
* Azure Knowledge: Comprehensive understanding of the Azure platform, including knowledge about its architecture, services, and security measures.
* Data Engineering: A strong background in data engineering, with thorough understanding of concepts like ETL (Extract, Transform, Load), data cleaning, data structures, and data warehousing.
* Azure Data Services: Hands-on experience with Azure data services like Azure SQL Database, Azure Data Factory, Azure Data Lake, and Azure Synapse Analytics.
* SQL Database Experience: Proficiency in SQL databases with the ability to write complex queries and procedures. Experience with Azure SQL Database is particularly important.
* DevOps Practices: Understanding of DevOps principles and CI/CD pipelines, and experience with tools like Azure DevOps or GitHub.
* Communication Skills: Ability to communicate effectively with both technical and non-technical stakeholders, understanding their needs and translating them into data solutions.
* Problem-solving Skills: The ability to troubleshoot and resolve technical issues, as well as strategize for long-term improvement.
* Understanding and experience working in Technology and Data teams in Asset Management, Investment Banking and general Financial Services sectors.
* Stakeholder Relationship Management: Experience working with different stakeholders, understanding their needs and communicating effectively. Proven ability to maintain strong stakeholder relationships.
* Big Data Technologies: Familiarity with big data technologies like Apache Spark, Hadoop. Even though they might not be needed directly, the understanding could help in broader data architecture discussions.
* Certifications: Additional relevant certifications like the Azure Solutions Architect Expert, Azure DevOps Engineer Expert, or certification in other BI tools like Tableau.
* Project Management: Experience with project management methodologies like Agile, Scrum, or Kanban, which can be useful in a team setting.