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

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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. 

 

Your key responsibilities 

• Design, develop, optimize, and maintain data architecture and pipelines that adheres to ETL principles and business goals 

• Develop and maintain scalable data pipelines, build out new integrations using AWS native technologies to support continuing increases in data source, volume, and complexity 

• Define data requirements, gather and mine large scale of structured and unstructured data, and validate data by running various data tools in the Big Data Environment 

• Support standardization, customization and ad hoc data analysis and develop the mechanisms to ingest, analyse, validate, normalize, and clean data 

• Write unit/integration/performance test scripts and perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues 

• Implement processes and systems to drive data reconciliation and monitor data quality, ensuring production data is always accurate and available for key stakeholders, downstream systems, and business processes 

• Lead the evaluation, implementation and deployment of emerging tools and processes for analytic data engineering to improve productivity 

• Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes 

• Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics 

• Solve complex data problems to deliver insights that help achieve business objectives 

• Implement statistical data quality procedures on new data sources by applying rigorous iterative data analytics 

• Strong understanding & familiarity with all Hadoop Ecosystem components and Hadoop Administrative Fundamentals 

• Strong understanding of underlying Hadoop Architectural concepts and distributed computing paradigms 

 

Skills and attributes for success 

• 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