Data Architect - Industrials & Energy Sector - Senior - Consulting - Location Open

US Consulting - AI & Data - Data Architect, Industrials & Energy Sector – Senior 

The opportunity  

EY is seeking a Data Architect with strong technology and data understanding having proven delivery capability. Lead the design, development, and management of the organization’s data architecture, ensuring scalable, efficient, and secure data solutions that align with business goals and support enterprise-wide data initiatives. 

In this role, you will create, maintain, and support the data platform and infrastructure that enables the analytics front-end; this includes the testing, maintenance, construction, and development of architectures such as high-volume, large-scale data processing and databases with proper verification and validation processes. 

• Experience in the development of Hadoop APIs and MapReduce jobs for large scale data processing 

• Hands-on programming experience in Apache Spark using SparkSQL and Spark Streaming or Apache Storm 

• Hands on experience with major components like Hive, Spark, and MapReduce 

• Experience working with NoSQL in at least one of the data stores - HBase, Cassandra, MongoDB 

• Experienced in Hadoop clustering and Auto scaling 

• Good knowledge in apache Kafka & Apache Flume 

• Knowledge of Spark and Kafka integration with multiple Spark jobs to consume messages from multiple Kafka partitions 

• Advanced experience and understanding of data/Big Data, data integration, data modelling, AWS, and cloud technologies 

• Strong business acumen with knowledge of the Industrial Products sector is preferred, but not required 

• Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata 

• Ability to build and optimize queries (SQL), data sets, 'Big Data' pipelines, and architectures for structured and unstructured data 

• Experience with or knowledge of Agile Software Development methodologies. 

• Demonstrated understanding and experience using: 

• Data Engineering Programming Languages (i.e., Python) 

• Distributed Data Technologies (e.g., Pyspark)  

• Cloud platform deployment and tools (e.g., Kubernetes) 

• Relational SQL databases  

• DevOps and continuous integration  

• AWS cloud services and technologies (i.e., Lambda, S3, DMS, Step Functions, Event Bridge, Cloud Watch, RDS) 

• Databricks/ETL 

• IICS/DMS 

• GitHub 

• Event Bridge, Tidal 

To qualify for the role you must have 

• Flexible and proactive/self-motivated working style with strong personal ownership of problem resolution 

• Excellent communicator (written and verbal formal and informal) 

• Ability to multi-task under pressure and work independently with minimal supervision. 

• Partner with Business Analytics and Solution Architects to develop technical architectures for strategic enterprise projects and initiatives 

• Coordinate with Data Scientists to understand data requirements, and design solutions that enable advanced analytics, machine learning, and predictive modelling 

• Support Data Scientists in data sourcing and preparation to visualize data and synthesize insights of commercial value 

• Collaborate with AI/ML engineers to create data products for analytics and data scientist team members to improve productivity 

• Advise, consult, mentor and coach other data and analytic professionals on data standards and practices, promoting the values of learning and growth 

• Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions 

Ideally, you’ll also have 

• Experience in leading and influencing teams, with a focus on mentorship and professional development 

• A passion for innovation and the strategic application of emerging technologies to solve real-world challenges 

• The ability to foster an inclusive environment that values diverse perspectives and empowers team members 

FY25CH