The company is seeking a Senior Data Engineer to build scalable data platforms and pipelines, specifically to support Data Science initiatives by transforming raw data into curated, model-ready features and establishing practices like feature stores for consistency, reuse, and experimentation.
Requirements
- 8+ years of experience delivering data-centric platforms with large datasets, fast SLAs, and high data quality standards.
- Advanced proficiency in Python, including data processing libraries (e.g., Pandas, PySpark).
- Strong hands-on experience with AWS data stack (S3, Glue, Athena, EMR, SageMaker) as well as orchestration and warehousing tools like Airflow and Snowflake.
- Proven track record building pipelines that support Data Science workflows, including feature engineering and model-ready datasets.
- Solid end-to-end development process experience, including CI/CD, automated deployments, code reviews, and delivering high-quality, production-ready code.
- Strong problem-solving skills with the ability to debug complex issues and optimize performance.
Responsibilities
- Design, build, and maintain scalable data platforms and pipelines using technologies like Python, Airflow, Snowflake, and AWS (S3, Glue, Athena, EMR, SageMaker), ensuring performant, reliable, and high-quality delivery.
- Partner closely with Data Scientists to transform raw data into curated, model-ready features, and establish practices such as feature stores to support consistency, reuse, and experimentation.
- Apply data quality, lineage, and governance practices to ensure datasets and features are trusted, reproducible, and well-documented.
- Produce clear technical documentation, including artifacts for testing, training, and delivery.
Other
- Strong collaboration skills
- Solid understanding of the financial services sector
- Collaborate with stakeholders across business, research, and technology teams to align on requirements, priorities, and outcomes.
- Excellent interpersonal and organizational skills, with the ability to work collaboratively across Data Science, Engineering, and Business teams.
- Bring drive and creativity to the role
