What youll do:
Develop end-to-end ETLs and data infrastructure features from data processing logic to database choice and implementation through to API development.
Improve the scalability and performance of existing data pipelines.
Delve into existing pipelines and business logic, target weaknesses and add functionality.
Mentor, advise, and work collaboratively within the Biz Data & Dev group, with other development teams, and with all other business teams of the company.
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible.
Collaborate on software-oriented projects as needed, bridging data engineering expertise with backend development work in a cross-functional environment.
3-5 years of experience in data engineering in Big Data environments
2+ years of experience with Spark and its ecosystem.
Experience using JVM stack, build tools, and environment (We mostly use Scala).
Experience with public cloud environments (AWS will be a bonus), Hadoop ecosystem, SQL and NoSQL databases.
High proficiency with Python and at least one JVM-based language (Scala, Java, or Kotlin).
Proficiency with SQL and experience with ETL and data modeling and development.
Positive attitude and willingness to take ownership.
A mindset of continuous learning and the desire to try new things.
Ability to see the "big picture" and to understand the business side of things.
Hands-on experience with modern AI tools (e.g., LLMs, code assistants) and a proactive curiosity to evaluate and integrate AI-driven solutions into data engineering practices- Advantage.
