Data Engineer at EY focusing on digital transformation projects in finance. Collaborating across teams to develop innovative data solutions in a diverse, global environment.
Responsibilities
Collaborate within multidisciplinary teams, communicating effectively to achieve shared objectives.
Work on resolving complex problems by developing creative and innovative solutions.
Apply critical thinking to analyze data, identify patterns, and make evidence-based decisions.
Pursue continuous learning, adapting to new technologies and trends to enhance your skills and contribute to project success.
Requirements
Bachelor's degree completed or in progress in Computer Science, Mathematics, Statistics, Economics, Business Administration, Engineering, or related fields.
Proficiency in Python for scripting, data manipulation, and ETL solutions.
Knowledge of SQL for querying and manipulating databases.
Proficiency with PySpark for data processing.
Experience with Apache Spark for large-scale data processing.
Knowledge of Hadoop for data storage and processing.
Experience using GitHub for version control and collaboration.
Knowledge of Power BI or other data visualization tools.
Nice-to-haves: Experience with ElasticSearch, domain knowledge of the financial sector, certifications in Cloud Computing and Databricks, and familiarity with DevOps tools and Generative AI.
Benefits
Visit go.ey.com/benefits to explore our range of benefits.
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