Lead Data Engineer

Responsibilities

• Design, build, and maintain resilient data pipelines ingesting data from Azure SQL, SaaS platforms, and event streams into BigQuery
• Write Python code using DLT to define declarative, testable, and version-controlled pipelines
• Build and operate low-latency, real-time ML feature pipelines
• Own operational health including monitoring, alerting, error handling, and incident response
• Collaborate with analytics engineers on schema design and data quality standards
• Partner with AI/ML platform teams to design feature stores and model serving pipelines
• Mentor junior engineers and participate in technical decisions regarding platform direction

Requirements

• 8+ years of professional software engineering experience
• 4-5 years in data engineering roles building pipelines at scale
• Hands-on experience with Modern Data Stack architectures (ingestion, warehouse, transformation, orchestration)
• Proficiency in Python for writing clean, testable, and maintainable code
• Fluent SQL with ability to optimize complex queries and execution plans
• Experience with cloud data platforms like BigQuery, Snowflake, or Redshift
• Experience with infrastructure-as-code tools such as Terraform, CloudFormation, or Pulumi
• Understanding of DevOps principles including observability and resilience

Preferred Qualifications

• Experience with DLT or similar declarative ELT frameworks
• Experience with Google Cloud Platform (BigQuery, Cloud Run, Pub/Sub, Dataflow)
• Experience with Kafka or other event streaming platforms
• Experience scaling data systems to 100M+ events per day
• Experience implementing data quality frameworks like Great Expectations
• Background in fintech or high-stakes data reliability environments

About the Company

Liberis is a growth-stage fintech building an embedded finance platform that enables partners to offer innovative funding products to small businesses. We are a global team focused on autonomy, ownership, and impact, currently undergoing an AI-first transformation.