Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.
As a member of our Data Engineering Group, we look first and foremost for people who are passionate about leveraging data to drive business outcomes through innovation and engineering practices. You will be expected to apply your depth of knowledge and expertise to all aspects of the data lifecycle, and to partner continuously with stakeholders to stay focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning.
You’ll work in a collaborative, trusting, and thought-provoking environment—one that encourages diversity of thought and creative solutions in the best interests of our customers globally. Our data engineers focus on the acquisition, transformation, and management of large-scale data assets, creating solutions that integrate seamlessly into existing architecture.
Job responsibilities
- Acquire and manage data from various sources and storage systems
- Transform existing ETL logic to AWS, Databricks, or equivalent cloud platforms
- Implement new or enhance existing services and components using both object-oriented and functional programming
- Establish and enforce guidelines to ensure consistency, quality, and completeness of data assets
- Analyze, design, and implement business solutions and core architectural changes using Agile methodologies within a development team
Required qualifications, capabilities, and skills
- Bachelor’s degree or equivalent experience
- Proficiency in one or more modern programming languages, including Python or Java (only one is required, but both is a major plus)
- Proficiency in Spark fundamentals and experience implementing Spark in data lake or data mesh solutions
- Experience with either AWS, Databricks or Snowflake
- Fluent in English
Preferred qualifications, capabilities, and skills
- Experience in AI is a plus
- Financial Services experience is a plus
- Experience with Infrastructure as Code (Terraform)
- Familiarity with relational and non-relational databases