Senior Analytics Engineer

Purpose of Job The Senior Analytics Engineer is a key role in the Data Analytics Team , one of six functions within the EMEA Data Office . This role will help to develop and mature analytical capabilities across SMBC EMEA. The focus of this role will be the creation of clean, scalable, and reusable datasets and data models that can be used and reused for a range of analytical purposes (dashboards, reports, models) to drive business decisions. As a practice lead, this role will provide leadership and guidance for other Analytics Engineers and Data Analysts within the Data Analytics team, the broader Data Office and across the EMEA Analytics Community ensuring that best practices and standards are adhered to. This role will also help to lead the rollout and adoption of Self-Serve Analytics by playing a key role in supporting the build out of the Analytics Centre of Excellence (COE) . A primary objective is to collaborate with internal stakeholders and enable them to harness their data assets and turn them into actionable insights which deliver business value. The role will require the successful candidate to collaborate with stakeholders across all functions, including department level analytics teams, to drive best practice and ensure fit-for-purpose analytics and insights is delivered across the organisation. The candidate must be willing to challenge the status quo in an empathic manner, while helping the wider Data Office team to have an ethos of openness and transparency that will help us nurture genuine business innovation. If you want to make a real difference, and not just in one team but across the entire bank, we would love to speak to you more. Background The EMEA Data Office was established in October 2021. It sits within EMEA Operations in the Operations Planning Department (OPPD), covering all EMEA entities (including Securities and Banking subsidiaries) and all datasets. The Data Office is responsible for defining and implementing the EMEA Data Strategy, building out its data management capabilities, and focusing on how we exploit data more effectively and innovatively across SMBC. We have been formed to really drive data-led transformation through the bank. As part of this work, the EMEA Data Office has established a new framework which encompasses cultural, behavioural, procedural, and system transformation to deliver the new strategy. This initially focused on good governance through improved Data Architecture, Data Management and Data Quality, but as the foundations are established, we are focusing more on how we can use Data to drive new ways of working and improved business outcomes. Facts/ Scale The EMEA Data Office has grown quickly to have over fifty members (a mixture of permanent employees, contractors, and consultants) in less than 3 years, and this is expected to grow further over the next 2-3 years. There are currently 11 people in Data Analytics Team within the EMEA Data Office, with another new role due to land soon, and we are expecting this team to grow further over the next 2-3 years. This role will be expected to matrix manage, supervise and/or coach other similar roles with the Data Analytics Team as well as providing mentoring, coaching and support for the wider Analytics Community. Accountabilities & Responsibilities To champion and be the expert on analytics engineering best practice with the ability to articulate “what good looks like” in establishing capability. Coaching & mentoring analysts in the Data Office and across SMBC EMEA departments as well as signposting appropriate training resources. Developing templates, best practice guidance and standards for use by the EMEA Analytics Community. Supporting the rollout and driving the adoption of Self-Serve Analytics Collaborating with the analysts embedded within business teams to help them create analytics outputs which will harness their data assets and turn them into actionable insights. Delivering new datasets and data models using best practice techniques to translate complex data into compelling outputs that help to answer important business questions. Identifying cross-functional use-cases which have the potential to deliver business value. Running proofs-of-concept to test feasibility and value, uncovering benefits for our stakeholders, customers, and businesses. Presenting and discussing interesting insights to the wider business. Working cross functionally with the wider data and technology teams, including analysts, engineers, project managers and product managers Coordinate with business process stakeholders to ensure that the business context and impacts are considered. Support the implementation of the EMEA Data Strategy Framework and helping to communicate the value the Data Analytics Team and the Data Office more broadly are delivering. Knowledge, Skills, Experience & Qualifications Essential: Experience establishing analytics capability, and in particular analytics engineering, for other organisations. Experience working in a data team and collaborating with cross-functional teams to identify, scope and develop data analytics solutions. An outstanding problem solver who is has an analytical mindset, is inquisitive and excellent with technology enabling a creative approach to solution scoping and delivery. Core competency in SQL along with proficiency in at least one other programming language e.g. R, Python Strong data manipulation, data preparation and data modelling skills along with solid experience of using a variety of relevant tools and techniques, this should ideally include Alteryx. Demonstrable experience of working on projects with diverse and complex data sets and all data types. Ability to manage analytics products using appropriate version control methods, experience using Git Repository would be a bonus. Demonstrable experience of training, mentoring and coaching others in the use of Analytics Engineering techniques and tooling. Solid understanding of the full Software Development Lifecycle (SDLC) Testing as relevant to analytics and ability to support the full project lifecycle for projects you work e.g.: requirements gathering, design approvals, development, testing, documentation requirements and release processes. Experience of applying appropriate testing methodologies for analytics engineering to quality assure development. Effective written and verbal communication skills: (i) comfortable presenting to and facilitating group of business users at all levels, (ii) ability to describe technical solutions to non-technical colleagues. A good understanding of core mathematical and statistical concepts A good understanding of, and experience of applying, project management principles and approaches like waterfall and agile. Experience of working in the financial services industry and knowledge of data related regulatory requirements for financial service sector. Ability to plan and manage own work to meet challenging deadlines with minimal supervision. The ideal candidate must be able to balance engagement and capability development effectively with analytics delivery work. Desirable: Experience with using Power BI and/or Tableau to develop data driven dashboards. Experience of statistical techniques and hands on statistical modelling experience, e.g. forecasting, regression analysis and probability distributions Experience of working in an organisation that has rolled out self-serve analytics tooling at enterprise level. Knowledge of emerging trends and issues within the Data Analytics and Data Science landscapes Experience with Microsoft Fabric, working with Azure cloud environments and Data Platforms like Denodo and Data Bricks would be a plus Challenges This is a greenfield opportunity where capability needs will be built from scratch. Patience and persistence are key attributes because significant business change is challenging. The ideal candidate will need to evidence a proactive engagement approach. There is limited understanding of the opportunities from new data and analytics capabilities, and therefore good project and communication skills are required