GenAI Big Data Engineer (Financial Services) Manager, Technology Consulting
Ernst and Young2 hours ago
Singapore, SingaporeStaff+
Responsibilities
- Participate in large-scale financial services client engagements.
- Contribute to or lead the delivery of innovative big data solutions.
- Understand business and technical requirements and provide big data engineering subject matter expertise.
- Conduct data discovery, root cause analysis, and recommendations for resolving data quality issues.
- Design, build, install, configure, deploy, administer, and support Hadoop-based applications.
- Explain analyses to clients and translate findings into clear business plans.
- Prioritize and complete multiple complex projects under tight deadlines.
Requirements
- Bachelor’s or master’s degree in computer science, engineering, or a related field.
- At least 6 years of relevant experience.
- Understanding or practical experience handling and manipulating semi-structured and unstructured data.
- Deep understanding of big data technologies, concepts, tools, features, functions, and implementation approaches.
- Experience with at least one of Java, Python, C#, or C++.
- Experience with ETL tools such as Talend, Informatica, AWS Glue, or Azure Data Factory; hands-on Talend experience is a plus.
- Hands-on experience with HiveQL.
- Familiarity with Kafka, Flume, Sqoop, and Oozie.
- Understanding of data modeling and entity-relationship modeling techniques.
- Experience investigating and handling data quality issues.
- Strong presentation, communication, business relationship, problem-solving, time management, and organizational skills.
- Preferred experience designing or implementing physical data models in SQL Server, Oracle, IBM DB2/Netezza, or Teradata.
- Preferred experience with business intelligence or statistical analysis tools and techniques.
- Candidates with more than 9 years of relevant experience may be considered for a Senior Manager position.
Benefits
- Continuous learning opportunities to develop new skills and capabilities.
- Tools and flexibility to make a meaningful impact and define success personally.
- Leadership development through insights, coaching, and confidence-building.
- Diverse and inclusive culture that supports employees’ voices and perspectives.
Tech Stack
Categories
Data Engineering