Data Engineer

Overview

• Develop and maintain scalable data pipelines and workflows supporting investment, research, and operational teams.
• Design and optimize data models and analytical datasets in Snowflake for business intelligence.
• Implement monitoring and alerting systems to ensure data quality and reliability.
• Collaborate with cross-functional teams to integrate data solutions across the organization.
• Contribute to the modernization of legacy systems using advanced technologies.
• Participate in code reviews and uphold engineering standards within the team.
• Support the adoption of containerization and cloud-native solutions for scalability.
• Engage in on-call rotations to maintain system reliability and performance.
• Actively identify and automate manual processes to enhance operational efficiency.

Key Responsibilities & Duties

• Develop and maintain data pipelines for ingesting, transforming, and delivering critical data.
• Create and manage data models in dbt, ensuring documentation and lineage tracking.
• Optimize analytical datasets in Snowflake to support reporting needs.
• Write and maintain Airflow DAGs and scripts using Python and SQL.
• Collaborate with engineering and analytics teams to deliver integrated solutions.
• Implement monitoring tools like Datadog to ensure data pipeline reliability.
• Translate business logic from legacy systems into modern data models.
• Contribute to the adoption of containerization and orchestration technologies.
• Participate in code reviews to maintain high-quality engineering practices.

Job Requirements

• Bachelor of Science (BS) degree in a relevant field.
• 3-5+ years of experience in data engineering roles.
• Proficiency in Python and SQL for production-level coding.
• Hands-on experience with Airflow, Snowflake, and SQL Server.
• Knowledge of dimensional modeling and data warehouse design patterns.
• Experience with dbt, Docker, Terraform, Azure, GitHub Actions, and Datadog preferred.
• Ability to work autonomously and proactively solve problems.
• Strong communication skills to explain technical concepts to non-technical stakeholders.
• Prior experience in wealth management or investment operations is advantageous.