Software Engineer III (Python, C#, AWS, Snowflake/Databricks and/or Go)

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Skills you'll use

What you'll do

• As a Senior Software Engineer with a strong background in data engineering, you will lead and deliver solutions that enable efficient vectorized data management and retrieval across our Snowflake and Databricks platforms. You will also mentor a growing team, collaborate with stakeholders and implement scalable data pipelines optimized for large-scale analytical and AI/ML workloads.
• Contribute end-to-end design, implementation, and optimization of data pipelines for vectorized data storage, transformation, and serving.
• Collaborate with cross-functional teams (data science, analytics, product) to define data requirements, architecture, and data models optimized for vector data.
• Deliver high-performance data solutions using Databricks (Spark, MLflow, Delta Lake) and Snowflake, leveraging vectorized storage and retrieval mechanisms.
• Develop robust ETL/ELT processes for large datasets, including data ingestion, feature extraction, and index building for vector similarity search.
• Enhance existing data platforms to support vector data workloads, integrating with LLM and other AI/ML services as needed.
• Ensure data governance, security, quality, and compliance with internal and external regulations.
• Mentor and lead other data/software engineers, fostering best practices in software craftsmanship and data engineering.
• Monitor, troubleshoot, and optimize data pipelines and processes for cost and performance.
• Stay on top of emerging technologies in vector databases, cloud data platforms, and AI/ML infrastructure.

Who can apply

• Bachelor's or Master's degree in Computer Science or Engineering or related field, or equivalent education.
• 3+ years of experience in system design for large-scale, distributed systems
• Great proficiency in Python, C#, AWS, Snowflake/Databricks and/or Go preferred programming
• Strong experience with cloud-native application development and cloud platforms (AWS/Azure/GCP)
• Hands-on experience with vector data storage, vector databases, and similarity search (e.g., ANN, Faiss, Pinecone, Milvus).
• Hands-on expertise with modern datalake and cloud data platforms such as Snowflake, Databricks, Redshift, or similar

About FactSet

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