Rockefeller Capital Management is looking for an AI/ML Data Engineer to design and implement scalable data solutions, ensuring performance and supporting business needs with reliable and secure data delivery, while also working at the intersection of data engineering and applied AI.
Requirements
- Experience with at least one major data platform: Databricks: Spark (PySpark/Scala), Delta Lake, notebooks (preferred).
- Microsoft Fabric: Lakehouse, Warehouse, Data Engineering pipelines, Power BI integration (preferred).
- Snowflake: SQL, performance tuning, data modeling.
- Proficiency in SQL and one programming language (Python, Scala, or Java).
- Exposure to machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and ML services (Azure ML, Databricks ML).
- Familiarity with Azure cloud services, DevOps practices, and CI/CD pipelines.
- Experience with Spark and Delta Lake for scalable data processing
Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines and data models using Microsoft Fabric, Databricks, or Snowflake.
- Build and optimize lakehouse and warehouse architectures to support analytics and reporting needs.
- Implement data governance practices including data quality, cataloging, lineage, and access controls.
- Integrate Azure data services (Data Factory, Synapse, Functions, Logic Apps) into workflows.
- Support Power BI integration for reporting and visualization across platforms.
- Contribute to CI/CD pipelines and version control for reliable deployments.
- Apply machine learning workflows using Azure ML or open-source frameworks (e.g., scikit-learn).
Other
- 4-5 years of hands-on experience in data engineering and analytics.
- 4-6 years of hands-on experience in data engineering or development.
- Strong communication and collaboration skills
- Problem-solving mindset and ability to work cross-functionally
- Adaptability and eagerness to learn emerging technologies
