Technical Data Analyst

Job title:

Technical Data Analyst

Company

Brewin Dolphin

Job description

RBC Brewin Dolphin is one of the UK’s leading independent providers of discretionary wealth management. We offer award-winning personalised wealth management services that meet the varied needs of over 100,000 account holders, including individuals, charities, and pension funds.We specialise in helping clients protect and grow their wealth by creating financial plans and investment portfolios that meet personal and professional ambitions and aspirations. Our services range from bespoke, discretionary investment management to retirement planning and tax-efficient investing.About this opportunityThe role is a hybrid one of system and data analyst and programmer which we refer to as Technical Data Analyst, it suits an individual that is comfortable moving across the full data stack to deliver either client-facing data products or improved data management for the products we’re building. Requiring the analysis of source data (including the systems and business processes that underpin), define data-centric requirements, and perform design and implementation to deliver data management, data products, or data insights within our Wealth business. Part systems analyst, part data analyst and part programmer: the technical data analyst.Responsibilities and activities include:

• Data Evangelist. Be a data & analytics evangelist who is passionate about data and using their expertise to provide insights and capability.
• Requirements. Define data-centric solution-focused requirements that are outcome driven using specific notations and tools (and are informed by the data).
• Data analysis & design. Identify business processes and systems that curate/maintain data to ensure that the data being sourced is trustworthy and reliable; make recommendations on data management and data quality improvements or produce targeted designs or supporting materials that deliver data products (reports, models, etc.).
• Data Exploration. Exploration and analysis of large volumes of complex data
• Hypothesis Testing. Creating and validating hypothesis using the data to answer business data questions
• Insights. Profile and analyze large volumes of data using modern data platforms using SQL, Power BI and Python.
• Data pipeline design. Review source data and inform data engineering of requirements for the acquisition of new data sources.
• Data modelling. Provide semantic and analytics models to conform source data to usable data models for reporting.
• Data management. Design appropriate structures and tools to improve the semantic understanding of data (Catalogues and Data Contracts), the protection of data (data classification) or the retention of data.
• Collaborate internally. Work closely with data engineers to specify solutions and deliver rapid insights and analytics to the business.
• Commercial. Work closely with client-facing and various business stakeholders (e.g. Operations, Finance, AML) to grow understanding of our business and identify opportunities with data [functional – bp, object models, etc. ]
• Visualization. Provide basic visualizations to aggregate or explain the data either past or predicative using ML/AI (working closely with Data Scientists or BI Specialists.
• Analytics applied Data Governance. Devise or align to several business-value driven data governance and information privacy initiatives, e.g. data privacy, security and access control, data retention, meta-data management (data catalogues). Use their awareness of what effective technical governance and ‘guardrail’ solutions around a Lakehouse solution are required.
• Agile Delivery. Comfortable working in an agile product data environment where data architecture & design is part of the delivery of an analytics capability to the business.
• Experience and Enthusiasm. Experience of modelling within a financial environment coupled to an enthusiasm for the business value which effective data distribution and data analytics can deliver for a market-leading wealth manager
• Flexible & Independent. The majority of the work will be within the Data & Analytics team who require accurate and certified datasets based on core data domain models and dimensional warehouse designs to drive insights.
• Integration and Migration. Support the definition of data migration strategies, integration, and master data management strategies to displace legacy systems incrementally provide OLTP integration or OLAP reporting solutions. Awareness of sourcing data in real-time or batch through various approaches and the impact on a data platform from a
• Educate and train. The technical data analyst should be curious and knowledgeable about new data initiatives and how to address them. This includes applying their data and/or domain understanding in addressing new data requirements. They will also be responsible for proposing appropriate (and innovative) data ingestion, preparation, integration and operationalization techniques in optimally addressing these data requirements
• Communication. Communicate efficiently, prepare well and use a variety of representations to convey ideas effectively.
• Teamwork. Help your team develop, both individually and collectively, through development conversations, coaching and feedback.
• You agree to comply with any reasonable instructions or regulations issued by the Company from time to time including those set out in the terms of the dealing and other manuals, including staff handbooks and all other group policies
• Deliver incrementally, meet and exceed expectations, and realize SMART objectives set by your manager.

Skills/Qualifications

• A bachelor’s or master’s degree in computer science, software engineering, statistics, applied mathematics, information systems, information science or a related quantitative field [or equivalent work experience] is preferred

• The ideal candidate will have a combination of software or data engineering skills, data analysis, and BI (or ML/AI) advanced analytics skills with a technical degree, or equivalent work experience

Personal skills and attributes:Mandatory:

• A great problem solver: technical, data or organizational

• Requirements and Analysis – experience in writing specifications in agile environment

• A passion for data and a technical understanding of data management, systems, processes, and tools

• Systems and technical data analysis and design with a software development background

• Database experience – highly proficient in SQL

• Software engineering experience – any modern functional or OO language (e.g. Java, Python, Scala)

• Data governance or data management experience including tools and frameworks preferred

• Excellent written and verbal communication skills including ability to distil a complex topic into presentations to senior stakeholders

Highly Desirable:

• Experience with wealth management preferred but not mandatory

• Experience working in in a business-facing analytics environment

• Coding and scripting background – both code review and relevant scripting experience ideally in Python.

• Familiar with using one or more data governance tools preferred (e.g., data quality, master data management, meta-data / data catalogues, data lineage, data modelling, data modelling, etc.)

• Familiar with using one or more data acquisition or ETL tools (e.g. Azure Data Factory, Five Trans, SSIS, etc.)

• Experience in creating requirements and design artefacts within an agile development environment

• Design skills such as entity relationship modelling, or class models ideally applied into a DWH or BI tool (e.g. Power BI)

• Familiar with broader industry standards on data protection (e.g. GDPR) and broad understanding of data protection requirements and controls for client data protection

• Worked on various database management technologies such as Relational Databases, Data Warehouse, Data Lake, Data Hub and the supporting processes like Data Integration, Governance, Metadata Management

• Cloud-based data platforms such as a Lakehouse (Databricks or Snowflake)

Interpersonal Skills and Characteristics

• Detail focused but strong communication skills. Able to get into detail but communicate complexity in plain English

• Experience supporting and working with cross-functional teams in a dynamic business environment.

• Required to be highly creative and collaborative. An ideal candidate would be expected to collaborate with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly. The successful candidate will also be required to have regular discussions with data consumers or producers on enhancing the design and with engineers or BI Analysts in implementing code.

• Required to have the accessibility and ability to interface with, and gain the respect of, stakeholders at all levels and roles within the company.

• Confident, energetic self-starter, with strong interpersonal skills.

• Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.

To apply for this role, please click the “Apply” button below. The closing date for applications is 24/06/2024. Some of our vacancies receive high numbers of applications and we may decide to close this sooner, so we would encourage you to apply as early as possible.

Expected salary

Location

London

Job date

Wed, 12 Jun 2024 05:25:19 GMT

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