Data Engineer - Industrials & Energy Sector - Staff - Consulting - Location OPEN

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.

 

US Consulting - AI & Data - Data Engineer, Industrials & Energy Sector – Staff

 

The opportunity

EY is seeking Data Engineers who will ingest, build, and support large-scale data architectures that serve multiple downstream systems and business users.

 

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, analyze, 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

 

Skills and attributes for success

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

 

To qualify for the role you must have

• Bachelor’s degree in Engineering, Computer Science, Data Science, or related field
• 1+ years of experience in software development, data science, data engineering, ETL, and analytics reporting development
• Exposure to designing, building, implementing, and maintaining data and system integrations using dimensional data modelling and development and optimization of ETL pipelines
• Proven track record of designing and implementing complex data solutions
• 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

• Strong organizational skills with the ability to manage multiple projects simultaneously and operate as a leading member across globally distributed tea