Our Partner is a subscriber-focused business intelligence company founded in 2001 that focuses on private investment markets in real estate, infrastructure, private equity, private debt, and specialist sector-specific activities within private asset classes.
We provide industry-leading journalism, data, and market insight to subscribing clients via a wide portfolio of specialist brands supported by our robust and scalable digital publishing, analytics, and database platform. With our multi-talented global team of over 400 people spread across EMEA, USA & Asia, our purpose is to inform and connect investment professionals across global, specialised markets.
As a Senior Data Analyst, you will play a crucial role in organising, analysing, and optimising our data infrastructure. Your primary responsibilities will include building and maintaining a comprehensive data catalogue, ensuring data quality, and collaborating with cross-functional teams to enhance our data platform capabilities. This role requires a strong analytical mindset, attention to detail, and a deep understanding of data governance principles.
Roles and responsibilities:
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Requirements Definition
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Collaborate with stakeholders from various departments (e.g., marketing, sales, business intelligence) to understand their data needs.
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Define and document requirements for expected datasets, specifying data elements, formats, security, access, and quality standards.
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Verify the accuracy, completeness, and reliability of source data
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Present proposed requirements and transformations for stakeholder review.
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Data Modeling
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Design and implement data models to represent and structure information for efficient storage and retrieval.
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Develop dimensional data models for analytics and reporting purposes, ensuring scalability and flexibility.
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Data Flow Mapping
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Create detailed data flow diagrams to illustrate the movement of data across systems and processes.
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Identify dependencies, transformations, and potential bottlenecks in data flows to optimise efficiency.
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Develop comprehensive mappings of current data flows, highlighting pain points, redundancies, and opportunities for optimization.
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Data Catalog Management
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Maintain and update data catalogues containing metadata descriptions of available datasets.
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Ensure data catalogue accuracy and relevance by documenting changes and additions to datasets.
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Issue Identification and Resolution
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Proactively identify data issues, anomalies, and opportunities for improvement through rigorous analysis.
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Collaborate with relevant teams to resolve data quality issues and optimise data processes.
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Document instructions for both manual interventions and automated solutions, promoting consistency and efficiency in problem-solving.
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Reporting and Visualisation
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Present findings and insights to stakeholders in a clear and visually appealing manner.
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Cross-functional Collaboration
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Work closely with data engineers, data scientists, and other stakeholders to ensure alignment on data initiatives and projects.
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Communicate effectively with non-technical stakeholders, translating complex technical concepts into understandable language.
Key Requirements:
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5+ years’ experience in a Data Analyst role as part of a transformation project or as a member of a data engineering or data science delivery team.
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5+ years experience with data analysis tools and reporting, also experience with RDBMS and dimensional data modelling.
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5+ years experience with SQL for data analysis, querying, and manipulation.
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Experience in identifying and defining requirements and turning them into functional requirements that address complex analytical challenges.
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Experience in solving data analytics problems and effectively communicating results and methodologies
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Knowledge of data, master data and metadata-related standards, processes and technologies
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Knowledge of (SDLC) methodologies (Agile methodology experience preferable).
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Strong communication and collaboration skills, with the ability to interact effectively with stakeholders at all levels.
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Ability to work independently and manage multiple tasks and priorities in a dynamic environment.
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Knowledge of alternative assets will be a plus.
Good to have:
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Experience in dashboard visualisation tools such as Tableau, Databricks Notebooks/Dashboards or Power BI is good to have.
