Public summary
Leading company in the software development industry seeks a Principal Data Engineer to drive the architecture, design, and implementation of large-scale data assets powering customer-facing analytics platforms. The role involves hands-on work with Snowflake, dbt, Airflow, and Terraform, setting technical direction, and mentoring senior engineers. Candidates must have over 10 years of experience in data engineering with strong architectural and leadership skills, especially in modern analytics stacks and AI-augmented engineering practices. The position offers a hybrid working model in a diverse and inclusive environment.
Responsibilities
Lead architectural alignment for customer-facing data assets; design and review high-impact data pipelines; translate complex architectural decisions for diverse stakeholders; establish and codify engineering best practices; drive transition to AI-first operational models; mentor and grow technical depth of teams; influence data governance, performance tuning, and cost optimization strategies.
Qualifications
Over 10 years in large-scale data engineering including 3+ years in principal or staff level roles with architectural ownership; deep expertise in Snowflake and modern analytics stack (dbt, Airflow, Apache Spark, Kafka, Terraform); strong knowledge of OLAP warehousing and data modelling methodologies; proficient in SQL and at least one programming language (Python preferred); proven leadership in technical design and decision-making; experience migrating enterprise platforms to cloud-native OLAP systems; familiarity with AI-augmented engineering workflows; excellent communication and problem-solving skills.