Data Engineer

Our client is a fast-growing, venture-backed technology company transforming a large, complex industry through artificial intelligence and modern data infrastructure. We’re building AI-powered products that combine advanced automation with human expertise to improve operational workflows, reduce friction, and create better customer experiences at scale. As an early-stage team, we’re focused on solving meaningful challenges using modern technology and creating a culture where ownership, innovation, and impact matter. We’re looking for a Data Engineer to build and scale the data foundations that power our platform, customer experience, analytics, and AI systems. The Role As a Data Engineer , you'll design and operate the infrastructure that moves, transforms, and structures data across our systems. You'll work across ingestion pipelines, transformation layers, monitoring, customer onboarding, and analytics while partnering closely with product, engineering, and AI teams. This is a hands-on role with meaningful ownership and the opportunity to influence how data architecture evolves as the business scales. Responsibilities Design and build reliable end-to-end data pipelines connecting customer systems, internal platforms, and AI-generated outputs Create and maintain transformation layers that convert raw data into trusted, documented datasets Develop dashboards and analytics solutions for both internal teams and customer-facing insights Implement monitoring, alerting, and data quality checks to proactively identify issues Lead customer data onboarding by mapping datasets and building scalable integration processes Improve performance and optimize warehouse costs as data volumes grow Collaborate with backend, AI, and product teams to align operational and analytical systems Establish best practices for data modelling, testing, documentation, schema management, and code review Support and improve AI-driven workflows and data capabilities Requirements 5+ years of experience in data engineering within production environments Strong Python and SQL skills Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, or similar Hands-on experience with transformation frameworks such as dbt or Spark Experience with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Databricks Strong understanding of data modelling principles across analytical and operational systems Experience with monitoring and data quality tooling Familiarity with CI/CD practices and testing for data workflows Comfortable working with emerging technologies, including AI-assisted development tools What We Offer Flexible working arrangements Competitive compensation and potential equity participation Modern tools and equipment Opportunities for rapid growth and meaningful impact Collaborative and highly talented team environment #J-18808-Ljbffr