Client Technology - Engineering - Data - Data Engineer - EY GDS (CABA, B, AR, 10

CT Senior Data EngineerRank: Assistant DirectorLocation: AnyEY is a global leader in assurance, tax, transaction and advisory services. Technology is at the heart of what we do and deliver at EY. Technology solutions are integrated into the client services we deliver and are key to our innovation as an organization.Fueled by strategic investment in technology and innovation, Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and powerful product engines that are vital to innovation at scale. As part of Client Technology, you’ll work with technologists and business experts, blending EY’s deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise. As a catalyst for change and growth, you’ll be at the forefront of integrating emerging technologies from AI to Data Analytics into every corner of what we do at EY. That means more growth for you, exciting learning opportunities, career choices, and the chance to make a real impact.The selected candidateNeeds to be hands-on with design and implementation of scalable data pipelines, ETL processes, and data warehousing solutions to align with Azure Well-Architected Framework (WAF) pillarsAccountable for a suite of data models with relatively high complexity, leveraging a strong understanding of data modelling standards to ensure high qualityDrive best practices for data security, data privacy, and data integrityEnsure the reliability and efficiency of data infrastructure in the Azure cloudUnderstands AI driven data engineering tools; and work on building cutting edge AI driven use cases and ensure availability of AI ready dataWorks with other departments across the business to help define and deliver business value, as well as interfacing and communicating with program teams, management and stakeholders to deliver large, complex projectsYour key responsibilities includeLeading the production of high-quality data engineering deliverables, helping to ensure project timelines are met, and providing informal mentoring / training to junior members of the teamLeading the design, development and implementation of processes to extract, transform and load data from disparate sources into a form that is consumable by analytics processes within a given project, reviewing deliverables to ensure high qualityDevelop and define future state data architectures aligned with industry best practices and organizational needsProficient in defining Data Strategy, developing data architecture for modern data platforms, assessing enterprise existing data architecture and devise recommendationsLeading translation of requirements, design and solution architecture deliverables into detailed design specificationsDefine and implement data management strategies to align with business objectivesLeading the delivery of data quality reviews including data cleansing where required to ensure integrity and qualityEvaluating and resolving issues regarding data quality reviews, cleansing, data integration and migration, leveraging advanced technical knowledge and showing technical leadership in aspects of data engineering while driving continuous improvement effortsProviding a leadership role for the work group, ensuring the appropriate expectations, principles, structures, tools and responsibilities are in place to deliver the projectAnalyzing the latest industry trends such as cloud computing and distributed processing and inferring potential impact on businesses (short and long-term)Providing advanced technical expertise to maximize efficiency, reliability and value from current data engineering processes. Researching and monitoring existing client base and industry developments to identify potential new product opportunities from emerging technologiesDeveloping strong working relationships with peers across engineering, collaborating to develop leading data engineering solutionsDriving adherence to the relevant data engineering and data modeling processes, procedures, standards, and may input into the definition, maintenance and implementation of technology standardsSkills and attributes for successData Architecture: Able to design and implement data architecture solutions that meet organizational needs by leveraging the Azure Well-Architected Framework (WAF) pillars (Cost Optimization, Operational Excellence, Performance Efficiency, Reliability, and Security)Infrastructure Architecture Diagrams: Able to create and deliver Azure Infrastructure Architecture Diagrams (IAD) that visually represent the architecture of data solutions, ensuring clarity and alignment with best practices.Data Extraction - Capability to design an efficient way of extracting high volumes structured and unstructured data with an automation CDC capability.Data Ingestion - Capability to design efficient ingestion strategy for batch processing as well as stream processing of all verity