Job descriptionFull Time
LandEarly 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.
What you'll do
- 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
What we're looking for
- 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, BigQuery, 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
Nice to have
- 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