Data Architect (San Francisco)

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Well 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.

The opportunity

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 in 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 engine that are vital to innovation at scale. As part of Client Technology, youll work with technologists and business experts, blending EYs deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise. As a catalyst for change and growth, youll 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

Your key responsibilities include

• 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 designing Data Architecture strategy, developing data architecture for modern data platform, 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

Skills and attributes for success

• 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 designs, develops and produces data models of relatively high complexity, leveraging a sound understanding of data modelling standards to ensure high quality.

• Data Store - Capability to designs data storage models, storage requirements and migration of data from one system to another.

• Data Consumption - Capability to designs data consumption mechanism with APIs, Virtualization and Visualization tools.

• Data Governance - Capability to designs a 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.

Required Technical Skills

• 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 and 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 speeds the performance of huge databases that deal with massive amounts of data

• Expertise in Azure, Azure Data Bricks, Azure SQL, Spark

• Expertise developing dataflows using NiFi/ADF, 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 and Kerberos

Beneficial Technical Skills

• 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

Education

• B.E. / M.S. Computer Science, Data Analytics, Data Science, Engineering, IT, or related field preferred

• Big Data Certification from either Cloudera/Hortonworks/Databricks

What we look for

• 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 criti]]>