About Louisa AI
Louisa AI, a cutting-edge institutional revenue enablement platform, was originally developed at Goldman Sachs and became an independent entity in 2023. It utilizes AI to maximize revenues by mapping the expertise and relationships within organizations, primarily serving financial institutions. Louisa AI emphasizes connecting people through AI, not replacing them, leveraging relationship graphs and news integration to enhance revenue generation and connections based on expertise, relationships, and relevant information.
Responsibilities:
As a data engineer on the Louisa team, you will have the opportunity to:
Data Architecture and Design:
- Design and implement scalable and efficient data models for storage and retrieval.
- Develop and maintain data architecture, ensuring optimal performance and data integrity.
ETL Development:
- Create and optimize ETL processes to extract, transform, and load data from various sources into the data warehouse.
- Implement data transformation logic to ensure data consistency and quality.
Programming and Scripting:
- Utilize programming languages (e.g., Python, Java) and scripting languages for data processing and manipulation.
- Develop custom code and scripts for data extraction, transformation, and loading tasks.
Data Quality and Governance:
- Implement data quality checks and measures to ensure accuracy and reliability.
- Adhere to data governance and security policies, ensuring compliance with relevant regulations.
Minimum Qualifications:
- Bachelor’s degree or relevant work experience in Computer Science, Mathematics, Electrical Engineering or related technical discipline.
- Minimum 5 years of relevant development experience.
- Strong proficiency in programming languages (e.g., Python, Java).
- Experience with big data technologies like Spark, Hive, etc and orchestration tool like airflow.
- Experience with Data warehousing tools like Snowflake/Big Query/Databricks SQL.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.
Extra awesome:
- Technical expertise with data models, data mining, and segmentation techniques
- Comfortable multi-tasking, managing multiple stakeholders and working in a global team.
