Semantic Data Model Engineer - Senior

Job Description

EY Consulting - Semantic Data Model Engineer and Analyst - SeniorTop 5 prerequisite skillsexperience for candidates to train up for this role, either:A software engineering backgroundSoftware engineering / computer science degree or professional qualificationPractically rather than theoretically minded ready to get hands on. E.g. keen coderExperience working with data in relational databases. Reasonable transact SQL knowledge.Experience working with XML and/or JSON filesExperience wrangling, transforming and analyzing datasetsAdvantageous if candidates have experience in these areasExperience in the finance/accountancy/tax domainsRESTful API consumption or designDatabase schema designUML modellingB: finance (incl. bookkeeping), accountancy, tax (incl. payroll) backgroundEntry level academic or professional qualification in finance, accountancy or tax-related disciplineExperience analysing and classifying data incl. very large and complex spreadsheetsPractically rather than theoretically minded ready to get hands on with complex IT things. Keen to learn to code and get under the hood.Advantageous if candidates have experience in these areasTechnology design or build experience. Software, services or APIs.Business process modelling, flow diagrams, etc.Designing data collection templates, forms or questionnairesJob Summary: Semantic Data Model AnalystEY is a global leader, driver and implementation partner of digitization programs. This is driven by a seismic change in the digital landscape: for example; Tax administrations are embracing APIs and establishing connected data ecosystems with industry and government, Capital Markets regulators are mandating electronic reporting, Auditors are increasingly making use of Artificial Intelligence, Machine Learning and data analytics. At the core of these changes is the effective use, management and sharing/reporting of data assets. The development and ongoing maintenance of data models is critical to the operation of EY s services, our clients businesses and the wider functions of industries and their market supervisors and governmental bodies.As a Semantic Data Model Engineer and Analyst you will become a member of EY s Global Data Office (GDO). Within the Intelligent Data Pillar (ID) you will report to the Data Standards and Models Leader (DSML) and the Data Management Lead (DML).You will support the day-to-day delivery of development, maintenance and extension of data models and data quality capabilities managed by the Global Data Office within EY s Trusted Data Fabric (TDF). Working closely with other Intelligent Data pillars Global Data Office including: Organization Intelligence (OrgIntel), Data Pipelines and Data Delivery.This hands-on role will support the team developing our data modelling and data quality services and underlying standards, principles and guidelines. You will support peers defining, enhancing or extending reference data taxonomies and business ontologies, physical data formats, definitions and structures to support business processes and service propositions. Covering semantic and logical presentations, data quality controls, as well as physical presentations for data transport, archive and analysis needs.This role will involve deep business analysis, as well as technical facilitation and presentation skills.Essential Functions of the Job:Work collaboratively as a member of project teams defining, enhancing or extending data formats, reference data taxonomies and business ontologies, physical data definitions, schemas and structures for tabular/relational data as well as object-oriented data models. Including aligned physical and analytical data models for common industry models, definitions, processes and standards.Support research and evaluation of external/alliance data standards/models.Focused on business analysis, interview and hold workshops with stakeholders to capture and document business-level semantic descriptions of business entities, business processes, logical relationships between facts and entities. Ensure that reference data taxonomies and business ontologies faithfully represent the semantic meaning intended by business stakeholders and that the models are understood need business entrants.Help capture data model comparability and interoperability requirements, to enable for example, the enrichment, reconciliation or comparison of client data with external/alliance data assets.Support data model lifecycle management and maintenance requirements. Including the development of enhancements to reference data taxonomies and data models in response to actual usage patterns and stakeholders needs.Ensure standards, policies and processes regarding data management are followed.Work with visual notations for expressing data logical and physical models, state transitions, transformation and versioning, data flows and business processes. Including UML, DPMN, ERDs, etc.Working knowledge of database design patterns, SQL, XML and JSON standards, data and data type transformations.Knowledge and Skills Requirements:Experience working with databases and data sets (Ontology, Taxonomy and Knowledge Graphs)Business analysis and intelligence experienceWorking knowledge of database design patterns, Incl. use of T-SQLIdeally experience working with XML and JSON data. Incl. data and data type transformations.Ability to analyze complex situations and to derive workable actionsAbility to constructively challenge requirements and current state to increase overall value to the firmStrong relationship building skillsAbility to understand and integrate cultural differences and motives and to lead virtual cross-cultural, cross-border teamsFlexibility to adjust to multiple demands, shifting priorities, ambiguity and rapid changeExcellent organization, written and verbal communicationDesirable, but not a prerequisite:Technical facilitating and training experience advantageousFamiliarity or experience with visual notations for expressing data logical and physical models, state transitions, transformation and versioning advantageous.Familiarity or experience with UML and software design methodologies advantageous.Familiarity of ERP systems, external reporting tooling, data templates and standards desirableFamiliarity of industry standard data models and open data standards desirableFamiliarity with cloud and data management trends desirableExperience working with data warehouse systems and enterprise data flow management systems for Hadoop, like FacebookApache Hive (incl. HiveQL) and Apache NiFi/NSA s Niagara Files desirableTeam Responsibilities:At EY we believe that it is important for the Data Office to be a multi-disciplinary. This requires that you demonstrate your ability to operate within a diverse team and expand your area of influence beyond traditional data management .Other Requirements:Moderate travelLong hours may occasionally be required to meet project commitments and/or preparing materials for clients (internal and external). Overtime may be required as per country overtime policyFlexibility in working hours to accommodate workload and multiple time zones, as neededEducation:A wide variety of degrees will be considered but a typical candidate may have a Bachelor s degree in a relevant domain such as Management Information Systems, Computer Science, Information Technology, Informatics or related technical field,However, work experience will be of equal, if not greater, importanceExperience:Overall 6 to 12 years of experience with a minimum of 1 year s relevant work experience in professional data-oriented roles, including:Hands-on experience of data analysis, reporting or data transformation projectsExperience processing external data sources and structured data formatsDemonstrated experience in business analysis and intelligence roles (with clear understanding of the use and application of data within business processes)Experience of having been engaged within a multi-cultural, multi-disciplined, globally dispersed teamSee above for knowledge and skill requirementsCertification Requirements:Any data analysis and data management Vendor or Industry certification is preferred but not mandatoryNote:This job description is intended as a guide to reflect the principal functions of the job. However, it is not an all-inclusive listing of the required job functions and functions may vary depending on the particular geographic location of the job and/or the manager. Further, the job description is subject to change at the discretion of management,

Keyskills :
design patternsdata modelingdata collectiondata managementdata analysisdata qualitydata transportdata standardsdata model engineer data modelsdata model engineer