Principal Data Engineer (Analytics)

Join our team as a Principal Data Engineer, where you will be at the forefront of building innovative data products that drive actionable insights and empower our internal teams and partners. You will have end-to-end ownership of the data product lifecycle, from conceptualization to production deployment, and will work closely with cross-functional stakeholders to translate domain-specific requirements into robust data solutions. Additionally, you will act as a mentor and technical resource for the team, conducting code reviews and providing guidance to junior and senior engineers.

• Assurer la propriété complète du cycle de vie des produits de données, de la conceptualisation initiale à la mise en production.
• Concevoir et coder des modèles dbt complexes et des logiques de transformation des données pour des ensembles de données financiers à fort volume.
• Agir en tant que leader technique pour des initiatives majeures, en gérant des projets de données complexes tout en restant actif dans la base de code.
• AI-Assisted Engineering: Proficiency in leveraging AI tools (e.g., GitHub Copilot,or similar LLMs) to accelerate code delivery, automate documentation, and optimize engineering workflows
• Experience implementing Airflow or similar orchestrators
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field
• Expert proficiency in SQL, with experience optimizing complex queries and data models at scale
• Experience treating data as software by implementing unit testing, CI/CD, comprehensive documentation, and SLA monitoring
• Experience architecting data models for FinTech and Capital Markets, including trade lifecycles, clearing/settlement, risk models, and financial reporting
• Experience using Databricks for analytics workloads, including building and optimizing data models using Databricks SQL and dbt
• Experience with dbt materializations, macros, and package management
• Ability to independently diagnose and resolve complex errors or issues within distributed systems (Spark/Databricks)
• Experience building Data Apps within Databricks
• Experience with Sigma Computing (from a data modeling perspective)
• 8+ years of professional experience in analytics engineering or data engineering, with a proven track record of building and scaling analytical data ecosystems
• Advanced proficiency in Python for data manipulation (Pandas/Polars/Spark) and interaction with APIs/AWS services
• Special Knowledge (Nice to Have, But Not Required)
• Proven ability to build data solutions that are reusable and modular, rather than one-off scripts
• Experience using AI/LLM tools to enable faster, smarter analytics workflows