Data Engineer

Land Early is looking for a Data Engineer to help build and maintain the data infrastructure that powers our job-matching and application platform. You'll work on the pipelines and systems that ingest, process, and serve data at scale, supporting features like real-time job matching, application tracking, and personalization.

• Design, build, and maintain scalable data pipelines to ingest and process large volumes of job posting and user data
• Develop and optimize ETL/ELT processes for structured and unstructured data sources
• Build and maintain data models, warehouses, and schemas that support analytics and product features
• Ensure data quality, reliability, and observability across pipelines through monitoring and testing
• Collaborate with backend engineers and data scientists to expose clean, well-documented datasets for matching and personalization features
• Optimize data infrastructure for performance and cost as data volume grows

• 3+ years of experience in data engineering or a related field
• Strong proficiency in SQL and at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java)
• Experience building and orchestrating data pipelines using tools such as Airflow, dbt, or similar
• Hands-on experience with cloud data warehouses (e.g., Snowflake, Big Query, Redshift) and cloud platforms (AWS, GCP, or Azure)
• Solid understanding of data modeling, schema design, and best practices for data quality
• Comfort working with both batch and streaming data processing

• Experience working with high-volume, real-time data systems
• Familiarity with event-driven architectures and message queues (e.g., Kafka)
• Exposure to machine learning pipelines or feeding data into ML models