EY Data Engineer 

Canada, Ontario, Toronto 

710614258

Our Data and Analytics practice provides expertise and delivery in four core areas of competency

• Data Management and Integration providing the foundational layers for enterprise data accessibility, covering data sourcing and integration, data warehouse and modelling, master data management and data rationalisation and migration. Design and implementation ETL solutions using one of the leading ETL packages (e.g., Informatica, Ab Initio, DataStage).
• Data Quality and Governance developing an organisation that treats data as a critical enterprise asset and sources quality data for business use and regulatory compliance. This includes examining the fitness for purpose of data for specific business needs, data remediation, and the strategy, roles, policies and processes to effectively manage data through its lifecycle;
• Reporting design, architecture and implementation of enterprise reporting solutions. This includes the end-to-end reporting lifecycle across advisory and strategy, identifying compliance reporting trouble spots and delivering achievable roadmaps, to vendor selection, design and implementation. Demonstrated experience and knowledge of at least one of the leading Business Intelligence Packages (e.g., Cognos, Business Objects, MicroStrategy, Tableau, SPSS, SAS); and
• Analytics covers operational analytics, predictive analytics, industry models and analytics enablement, and provides actionable enterprise insight and delivers value from an enterprises data. The area of Analytics and Data Science is expected to be a key driver for growth in the coming year.

Your key responsibilities

As a Data Engineer, you will:

• Lead event stream analytics initiative and create the foundation for event data collection at EY Canada.
• Design and build highly scalable and responsive platform to collect the data across all the brands and all devices (mobile apps, desktop …)
• Work with teams across EY to drive the new platform adoption

Skills and attributes for success

• Strong analytical and creative thinking skills, must be a team player

To qualify for the role you must have

• CS Degree or equivalent experience
• Databricks
• Data Platform
• Data Engineering
• 5-10 years of experience building and shipping highly scalable clickstream data pipelines and analytics systems on distributed data systems and cloud platforms (AWS/Azure/GCP)
• Experience with Java, Scala, Python etc.
• Solid experience in streaming technologies like Kafka or Spark Streaming.
• Experience building batch, real-time and streaming analytics pipelines with data from event data streams, NoSQL and APIs.
• Experience with batch & stream processing technologies such Spark, KStreams, Samza etc.

Ideally, you’ll also have

• Experience with ETL tools/ ETL flows with complex Transformations/Routines using Python, PySpark, Java, Javascript, Bash Shell Scripting;
• User interface and query software (IBM DB2);
• Enterprise application integration software (e.g. XML);
• Data modeling tools (ERWin, Enterprise Architect and Visio);
• Experience in business intelligence fields - strong analytical skills with the ability to collect, analyze, design and disseminate significant amounts of information with high attention to detail and accuracy;
• Application server software (Oracle)
• Exceptional Database management - SQL skills/experience using MS SQL Server, MySQL, SSIS, SSMS, SQL Server Management Studio, PostgreSQ;
• Advanced skill in Scala
• Applied knowledge in Big Data platforms, ideally with exposure to Hadoop ecosystem (HDFS, Pig, Hive, SPARK, Big SQL, NoSQL, YARN);
• Experience in designing efficient and robust pipelines.

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.