Principal Data Engineer

About the role

This full-time role focuses on designing and building enterprise-scale, real-time data platforms that power mission-critical financial applications. It is a highly visible technical leadership opportunity where you'll drive the architecture and modernization of next-generation streaming data platforms while mentoring engineers and influencing engineering standards across the organization.

Responsibilities

• 40% Real-Time Data Platform & Streaming Engineering
• 30% Cloud Infrastructure, Microservices & Distributed Systems
• 20% Architecture, Technical Leadership & Platform Modernization
• 10% Observability, Performance Optimization & CI/CD

Requirements

• 8+ years of experience in data engineering, software engineering, or backend platform development
• Expert-level Python development for data processing, automation, and scalable backend applications
• Advanced SQL skills including complex query development, CTEs, window functions, performance tuning, and query optimization
• Extensive experience designing and building scalable ETL/ELT pipelines and distributed data processing systems
• Strong experience with cloud-native data platforms on AWS, including Redshift, S3, Lambda, Glue, and related services
• Experience with Apache Kafka and event-driven data architectures
• Experience building and orchestrating batch and streaming data pipelines using tools such as Airflow, Spark, or Flink
• Strong knowledge of relational databases including PostgreSQL, Oracle, Amazon Redshift, and Aurora, with expertise in schema design and data modeling
• Experience with containerization and Infrastructure as Code using Docker, Kubernetes, Terraform, or CloudFormation
• Experience building CI/CD pipelines and implementing engineering best practices for production data platforms
• Experience implementing monitoring, logging, data quality, and observability solutions across enterprise data environments
• Proven ability to lead technical initiatives, mentor engineers, and collaborate across cross-functional engineering teams

Qualifications

Required Skills & Experience

Skills

Expert-level Python development for data processing, automation, and scalable backend applications

Advanced SQL skills including complex query development, CTEs, window functions, performance tuning, and query optimization

Extensive experience designing and building scalable ETL/ELT pipelines and distributed data processing systems

Strong experience with cloud-native data platforms on AWS, including Redshift, S3, Lambda, Glue, and related services

Experience with Apache Kafka and event-driven data architectures

Experience building and orchestrating batch and streaming data pipelines using tools such as Airflow, Spark, or Flink

Strong knowledge of relational databases including PostgreSQL, Oracle, Amazon Redshift, and Aurora, with expertise in schema design and data modeling

Experience with containerization and Infrastructure as Code using Docker, Kubernetes, Terraform, or CloudFormation

Experience building CI/CD pipelines and implementing engineering best practices for production data platforms

Experience implementing monitoring, logging, data quality, and observability solutions across enterprise data environments

Proven ability to lead technical initiatives, mentor engineers, and collaborate across cross-functional engineering teams

Benefits

The offer includes medical insurance, dental benefits, vision benefits, a 401(k) with company match, paid time off (PTO), paid holidays, paid parental leave, professional development reimbursement, and a hybrid work environment.