Principal Data Analytics Engineer

Required

• 8+ years of professional experience in analytics engineering or data engineering, with a proven track record of building and scaling analytical data ecosystems.
• Expert proficiency in SQL, with experience optimizing complex queries and data models at scale.
• Advanced proficiency in Python for data manipulation (Pandas/Polars/Spark) and interaction with APIs/AWS services.
• 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.
• Experience architecting data models for FinTech and Capital Markets, including trade lifecycles, clearing/settlement, risk models, and financial reporting.
• 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.
• Proven ability to build data solutions that are reusable and modular, rather than one-off scripts.
• Experience treating data as software by implementing unit testing, CI/CD, comprehensive documentation, and SLA monitoring.
• Ability to independently diagnose and resolve complex errors or issues within distributed systems (Spark/Databricks).
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.
• Special Knowledge (Nice to Have, But Not Required)