Jobs

Senior Analytics Engineer


Job details
  • Sumitomo Mitsui Banking Corporation – SMBC Group
  • London
  • 3 days ago

Purpose of Job The Senior Analytics Engineer is a keyrole in the Data Analytics Team, one of six functions within theEMEA Data Office. This role will help to develop and matureanalytical capabilities across SMBC EMEA. The focus of this rolewill be the creation of clean, scalable, and reusable datasets anddata models that can be used and reused for a range of analyticalpurposes (dashboards, reports, models) to drive business decisions.As a practice lead, this role will provide leadership and guidancefor other Analytics Engineers and Data Analysts within the DataAnalytics team, the broader Data Office and across the EMEAAnalytics Community ensuring that best practices and standards areadhered to. This role will also help to lead the rollout andadoption of Self-Serve Analytics by playing a key role insupporting the build out of the Analytics Centre of Excellence(COE). A primary objective is to collaborate with internalstakeholders and enable them to harness their data assets and turnthem into actionable insights which deliver business value. Therole will require the successful candidate to collaborate withstakeholders across all functions, including department levelanalytics teams, to drive best practice and ensure fit-for-purposeanalytics and insights is delivered across the organisation. Thecandidate must be willing to challenge the status quo in anempathic manner, while helping the wider Data Office team to havean ethos of openness and transparency that will help us nurturegenuine business innovation. If you want to make a real difference,and not just in one team but across the entire bank, we would loveto speak to you more. Background The EMEA Data Office wasestablished in October 2021. It sits within EMEA Operations in theOperations Planning Department (OPPD), covering all EMEA entities(including Securities and Banking subsidiaries) and all datasets.The Data Office is responsible for defining and implementing theEMEA Data Strategy, building out its data management capabilities,and focusing on how we exploit data more effectively andinnovatively across SMBC. We have been formed to really drivedata-led transformation through the bank. As part of this work, theEMEA Data Office has established a new framework which encompassescultural, behavioural, procedural, and system transformation todeliver the new strategy. This initially focused on good governancethrough improved Data Architecture, Data Management and DataQuality, but as the foundations are established, we are focusingmore on how we can use Data to drive new ways of working andimproved business outcomes. Facts/ Scale The EMEA Data Office hasgrown quickly to have over fifty members (a mixture of permanentemployees, contractors, and consultants) in less than 3 years, andthis is expected to grow further over the next 2-3 years. There arecurrently 11 people in Data Analytics Team within the EMEA DataOffice, with another new role due to land soon, and we areexpecting this team to grow further over the next 2-3 years. Thisrole will be expected to matrix manage, supervise and/or coachother similar roles with the Data Analytics Team as well asproviding mentoring, coaching and support for the wider AnalyticsCommunity. Accountabilities & Responsibilities - To championand be the expert on analytics engineering best practice with theability to articulate “what good looks like” in establishingcapability. - Coaching & mentoring analysts in the Data Officeand across SMBC EMEA departments as well as signposting appropriatetraining resources. - Developing templates, best practice guidanceand standards for use by the EMEA Analytics Community. - Supportingthe rollout and driving the adoption of Self-Serve Analytics -Collaborating with the analysts embedded within business teams tohelp them create analytics outputs which will harness their dataassets and turn them into actionable insights. - Delivering newdatasets and data models using best practice techniques totranslate complex data into compelling outputs that help to answerimportant business questions. - Identifying cross-functionaluse-cases which have the potential to deliver business value. -Running proofs-of-concept to test feasibility and value, uncoveringbenefits for our stakeholders, customers, and businesses. -Presenting and discussing interesting insights to the widerbusiness. - Working cross functionally with the wider data andtechnology teams, including analysts, engineers, project managersand product managers - Coordinate with business processstakeholders to ensure that the business context and impacts areconsidered. - Support the implementation of the EMEA Data StrategyFramework and helping to communicate the value the Data AnalyticsTeam and the Data Office more broadly are delivering. Knowledge,Skills, Experience & Qualifications Essential: - Experienceestablishing analytics capability, and in particular analyticsengineering, for other organisations. - Experience working in adata team and collaborating with cross-functional teams toidentify, scope and develop data analytics solutions. - Anoutstanding problem solver who is has an analytical mindset, isinquisitive and excellent with technology enabling a creativeapproach to solution scoping and delivery. - Core competency in SQLalong with proficiency in at least one other programming languagee.g. R, Python - Strong data manipulation, data preparation anddata modelling skills along with solid experience of using avariety of relevant tools and techniques, this should ideallyinclude Alteryx. - Demonstrable experience of working on projectswith diverse and complex data sets and all data types. - Ability tomanage analytics products using appropriate version controlmethods, experience using Git Repository would be a bonus. -Demonstrable experience of training, mentoring and coaching othersin the use of Analytics Engineering techniques and tooling. - Solidunderstanding of the full Software Development Lifecycle (SDLC)Testing as relevant to analytics and ability to support the fullproject lifecycle for projects you work e.g.: requirementsgathering, design approvals, development, testing, documentationrequirements and release processes. - Experience of applyingappropriate testing methodologies for analytics engineering toquality assure development. - Effective written and verbalcommunication skills: (i) comfortable presenting to andfacilitating group of business users at all levels, (ii) ability todescribe technical solutions to non-technical colleagues. - A goodunderstanding of core mathematical and statistical concepts - Agood understanding of, and experience of applying, projectmanagement principles and approaches like waterfall and agile. -Experience of working in the financial services industry andknowledge of data related regulatory requirements for financialservice sector. - Ability to plan and manage own work to meetchallenging deadlines with minimal supervision. The ideal candidatemust be able to balance engagement and capability developmenteffectively with analytics delivery work. Desirable: - Experiencewith using Power BI and/or Tableau to develop data drivendashboards. - Experience of statistical techniques and hands onstatistical modelling experience, e.g. forecasting, regressionanalysis and probability distributions - Experience of working inan organisation that has rolled out self-serve analytics tooling atenterprise level. - Knowledge of emerging trends and issues withinthe Data Analytics and Data Science landscapes - Experience withMicrosoft Fabric, working with Azure cloud environments and DataPlatforms like Denodo and Data Bricks would be a plus Challenges -This is a greenfield opportunity where capability needs will bebuilt from scratch. Patience and persistence are key attributesbecause significant business change is challenging. The idealcandidate will need to evidence a proactive engagement approach. -There is limited understanding of the opportunities from new dataand analytics capabilities, and therefore good project andcommunication skills are required

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