Data Analytics Engineer
About the Role
Join a seasoned Data Analytics Team, where you'll help build and maintain powerful analysis tools that scale across the organization. These tools support mission-critical trading operations, so reliability and performance are paramount. They're looking for someone who pairs a DevOps mindset with a research-driven, engineering-first approach.
Key Responsibilities
- Develop and implement new analytical tools by deeply understanding cross-functional business needs.
- Apply robust engineering practices and R&D expertise to deliver stable and scalable distributed and streaming data systems.
- Scale analytics tools from proof-of-concept to full production, running in both on-premise and cloud environments.
Required Skills & Experience
- 5+ years of Python development, with strong command of OOP, functional, and asynchronous programming styles.
- 3+ years working with containerized apps and orchestration platforms-ideally Docker and Kubernetes.
- Solid background in CI/CD pipelines and ownership of projects throughout the development lifecycle.
- Hands-on experience with AWS or GCP, including infrastructure-as-code using Terraform or Open Tofu.
- Deep understanding of data storage solutions-relational, NoSQL, and key-value databases.
- Familiarity with Apache Big Data formats and tools like Hadoop, Iceberg, Parquet, Arrow.
- Knowledge of distributed computing frameworks such as Dask, Ray, Spark, or Slurm.
- Experience with stream processing systems like Kafka, Flink, Beam, or similar.
- Exposure to machine learning platforms such as TensorFlow and XGBoost is a plus.
FAQs
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