Principal Data Engineer

This leadership role is crucial in shaping the architecture, design, and delivery of scalable, high-performance data solutions that power analytics, machine learning, and operational workloads across the organization. This Principal Data Engineer will serve as a technical leader, mentor, and strategic partner - guiding cross-functional teams through complex data initiatives and ensuring alignment with our long-term data strategy. You will partner closely with data scientists, analysts, platform engineers, and collaborators to create resilient and future-ready data pipelines and systems. A day in the life of a Principal Data Engineer : Architect and Design : Lead the architectural design and development of scalable data pipelines and systems End-to-End Data Ownership : Oversee the entire data lifecycle—from ingestion to consumption—ensuring quality, reliability, and performance. Technology Leadership : Drive best practices in our stack, including Snowflake, DBT, Airflow, Confluent Kafka, and Databricks, across AWS and Azure cloud platforms. Mentorship and Guidance : Provide technical leadership and mentorship to data engineers; establish coding standards, conduct peer reviews, and promote knowledge sharing practices. Lead and participate in pull request reviews to uphold engineering standards and mentor contributors. Innovation & Strategy : Evaluate emerging technologies and make recommendations to enhance our data infrastructure and strategy. 5+ years of hands-on experience in data engineering or a related field, with at least 3 years in a lead or principal role. Expert knowledge in : Data Lake & Warehousing : Snowflake, Databricks (Delta Lake), or equivalent ETL / ELT & Transformation : DBT, Spark Orchestration : Airflow, Databricks Asset Bundles Streaming : Confluent Kafka, Kafka Streams, or equivalent Cloud Platforms : Strong experience with AWS and Azure Strong proficiency in SQL and Python Familiarity with CI / CD and infrastructure-as-code principles. Proven track record of leading multi-functional technical initiatives and mentoring engineers. Proficiency in integrating AI solutions into new and existing technologies to improve efficiency, streamline operations, and elevate the consumer experience is required. Self-starter with a passion and curiosity for solving unstructured data problems and ability to manipulate and optimize large data sets. Knowledge of metadata management, data lineage, and principles of data governance. Hands-on experience with real-time data processing and event-driven architectures Excellent written and verbal communication skills - experience working with business and senior leaders. Bachelor's or master's degree in computer science, information systems or related field.