Job Description

At EY, you\xe2\x80\x99ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we\xe2\x80\x99re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.
CT Data Engineer
The selected candidate

• 
  Leads the delivery of processes to extract, transform and load data from disparate sources into a form that is consumable by analytics processes, for projects with moderate complexity, using strong technical capabilities
• Designs, develops and produces data models of relatively high complexity, leveraging a sound understanding of data modelling standards to ensure high quality
• Builds networks with other departments across the business to help define and deliver business value, and may interface and communicate with program teams, management and stakeholders as required to deliver small to medium-sized 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 delivery of data quality reviews including data cleansing where required to ensure integrity and quality
• Leading the delivery of data models, data storage models and data migration to manage data within the organization, for a small to medium-sized project
• Resolving escalated design and implementation issues with moderate to high complexity
• Analyzing the latest industry trends such as cloud computing and distributed processing and beginning to infer risks and benefits of their use in business
• Providing technical expertise to maximize value from current applications, solutions, infrastructure and emerging technologies and seek to continuously improve internal processes
• Developing working relationships with peers across other engineering teams and beginning to collaborate to develop leading data engineering solutions
• Driving adherence to the relevant data engineering and data modelling processes, procedures and standards

Skills and attributes for success

• 
  Batch Processing - Capability to design an efficient way of processing high volumes of data where a group of transactions is collected over a period of time
• Data Integration (Sourcing, Storage and Migration) - Capability to design and implement models, capabilities and solutions to manage data within the enterprise (structured and unstructured, data archiving principles, data warehousing, data sourcing, etc.). This includes the data models, storage requirements and migration of data from one system to another
• Data Quality, Profiling and Cleansing - Capability to review (profile) a data set to establish its quality against a defined set of parameters and to highlight data where corrective action (cleansing) is required to remediate the data
• Stream Systems - Capability to discover, integrate, and ingest all available data from the machines that produce it, as fast as it\xe2\x80\x99s produced, in any format, and at any quality

Category Tool Vendor Must have/Nice to have Level of proficiency

• Agile / Backlog / Project Management Tools
• Azure DevOps
• Microsoft

Must have Basic

• Big Data Distributed Systems
• Azure Data Lake Storage Gen2
• Microsoft

Nice to have Basic

• Big Data Distributed Systems
• Azure Databricks
• Microsoft

Nice to have Basic

• Big Data Distributed Systems
• Azure Synapse Analytics
• Microsoft

Nice to have Basic

• Big Data Distributed Systems
• Cloudera Data Platform
• Cloudera

Nice to have Basic

• Big Data Distributed Systems
• Databricks
• Databricks

Nice to have Basic

• Big Data Distributed Systems
• Delta Lake
• Databricks

Nice to have Basic

• Big Data Distributed Systems
• Hive
• Cloudera

Nice to have Basic

• Big Data Distributed Systems
• Spark
• Open source

Must have

• Intermediate
• Data Warehousing Platforms
• Azure SQL Warehouse / Azure Synapse
• Microsoft

Nice to have Basic

• Document Database
• MongoDB
• MongoDB

Nice to have Basic

• ETL / ELT / Data Fabric Tools
• Azure Data Factory
• Microsoft

Nice to have Basic

• Graph Databases
• Neo4j
• Neo4j

Must have

• Intermediate
• Programming Languages
• Java

Education

• 
  B.S. in Actuarial, Behavior Economics, Computer Science, Data Analytics, Data Science, Econometrics, Engineering, IT, Cyber Security, or related field preferred

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 critical times and tough circumstances
• Attention to detail
• High levels of integrity and honesty

EY | Building a better working world

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.