Client Technology - Engineering - Data - Data Engineer

About the position At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. EY 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 candidate Needs 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) pillars Accountable for a suite of data models with relatively high complexity, leveraging a strong understanding of data modelling standards to ensure high quality Drive best practices for data security, data privacy, and data integrity Ensure the reliability and efficiency of data infrastructure in the Azure cloud Understands AI driven data engineering tools; and work on building cutting edge AI driven use cases and ensure availability of AI ready data Works 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 projects Responsibilities • Leading 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 team • Leading 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 quality • Develop and define future state data architectures aligned with industry best practices and organizational needs • Proficient in defining Data Strategy, developing data architecture for modern data platforms, assessing enterprise existing data architecture and devise recommendations • Leading translation of requirements, design and solution architecture deliverables into detailed design specifications • Define and implement data management strategies to align with business objectives • Leading the delivery of data quality reviews including data cleansing where required to ensure integrity and quality • Evaluating 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 efforts • Providing a leadership role for the work group, ensuring the appropriate expectations, principles, structures, tools and responsibilities are in place to deliver the project • Analyzing 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 technologies • Developing strong working relationships with peers across engineering, collaborating to develop leading data engineering solutions • Driving adherence to the relevant data engineering and data modeling processes, procedures, standards, and may input into the definition, maintenance and implementation of technology standards Requirements • Data 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 of source data that produces on the transactional systems as fast as it is. • Data Processing - Capability to design and implement models, capabilities and solutions to process data within the enterprise (data validation, data quality, data profiling, etc.) • Data Modeling - Capability to design, develop and produce data models of relatively high complexity, leveraging a sound understanding of data modelling standards to ensure high quality. • Data Store - Capability to design data storage models, storage requirements and migration of data from one system to another. • Data Consumption - Capability to design data consumption mechanisms with APIs, Virtualization and Visualization tools. • Data Governance - Capability to design governance mechanism including data catalogue, lineage, classification, MDM, exploration. • Data Security: Able to design and implement various authentication and authorization methods to ensure Data security • Data Integration: Develop and manage data integration strategies, including ETL processes, to ensure seamless data flow and accessibility across systems. • Handson experience in building Data Architecture using various data architecture patterns like Data Mesh, Data Fabric, Data Lakehouse, Data observability & Data as a Service (DaaS) • Proficient in Azure services (e.g., Azure Data Lake, Azure SQL Database, Azure Synapse Analytics) to build scalable and efficient data solutions. • Experience in building data orchestration through Azure Data Factory, Function App, Logic App. • Proficient in SQL and familiar with programming languages such as Python or Java • Extensively worked on Databricks performance optimization (includes data Ingestion, transformation and consumption areas) • Experience designing and building Data Platforms integrating disparate data sources • Experience in design and development of various authentication and authorization methods to ensure data security. • Expertise in working with MPP designs to speed the performance of huge databases that deal with massive amounts of data • Expertise in Azure, Azure Databricks, Azure SQL, Spark • Expertise developing dataflows using ADF and/or Databricks • Advanced, hands-on design and implementation experience of large analytic warehouse. • Advanced, hands-on experience in Spark architecture and implementation using several methods • Experience in working with Distributed Message Systems like Kafka. • Hands on experience on Python, PySpark or R. • Expert in creating and analyzing complex SQL queries and procedures. • Understanding of big data and distributed Architecture. • Creating Ingestion workflows using Oozie or similar tools • Knowledge of security measures like HTTPS and Kerberos • Strong analytical skills and problem-solving ability • A self-starter, independent-thinker, curious and creative person with ambition and passion • Excellent inter-personal, communication, collaboration, and presentation skills • Customer focused • Excellent time management skills • Positive and constructive minded • Takes responsibility for continuous self-learning • Takes the lead and makes decisions in critical times and tough circumstances • Attention to detail • High levels of integrity and honesty Nice-to-haves • Azure Data Lake Store, Databricks Delta Lakes • Experience using NoSQL databases • Advanced Analytics, ML and AI • Knowledge in Graph Databases, preferably Neo4J, Cypher and CosmosDB • Experience developing Microservices Benefits • We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. • The base salary range for this job in all geographic locations in the US is $122,200 to $228,600. • The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $146,700 to $259,700. • Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. • In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. • Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. • You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being. 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