Data Engineer

About the Role As a Data Engineer, you will design, develop, and maintain reliable data pipelines and data systems that enable Data Science, Engineering, Product, and Operations teams to make data-driven decisions. You will work with large and diverse datasets across customers, vehicles, inventory, pricing, sales, marketplace activity, and operational systems. What You’ll Do Design, build, and maintain scalable ETL/ELT data pipelines . Develop reliable batch and near-real-time data ingestion workflows. Integrate data from internal applications, third-party APIs, databases, and other sources. Build and maintain data models for analytics, reporting, machine learning, and AI applications. Write efficient and maintainable SQL and Python code. Work closely with Data Scientists and Software Engineers to provide high-quality datasets for modeling and product development. Implement data-quality checks, monitoring, validation, and observability. Optimize data pipelines for performance, scalability, reliability, and cost. Build and maintain data warehouses and analytical infrastructure. Support data governance, security, lineage, and access controls. Troubleshoot data pipeline failures and resolve data-quality issues. Establish and maintain documentation for datasets, pipelines, and data architecture. Help develop the data foundation required for Ever’s AI-native automotive platform. Required Qualifications 3+ years of experience in Data Engineering or a closely related role. Strong proficiency in Python and SQL . Experience designing and building production-grade ETL/ELT pipelines. Experience with relational databases and data warehousing. Experience working with cloud-based data infrastructure. Strong understanding of data modeling and database design. Experience with data quality, validation, monitoring, and pipeline reliability. Ability to work effectively with Data Scientists, Software Engineers, Product, and business teams. Strong problem-solving and debugging skills. Preferred Qualifications Experience with Snowflake, BigQuery, Redshift, or Databricks . Experience with AWS or another major cloud platform. Experience with Airflow, Dagster, Prefect, or similar orchestration tools . Experience with dbt . Experience with Spark or other distributed data-processing technologies. Experience building real-time or streaming data pipelines. Experience with Kafka or similar event-streaming platforms. Experience supporting machine-learning or AI workloads. Experience with automotive, e-commerce, marketplace, mobility, or other high-volume transactional data. Experience working at an early-stage or high-growth technology company. What We’re Looking For Strong ownership and attention to data reliability. Ability to design simple, scalable solutions to complex data problems. Strong engineering fundamentals and clean coding practices. Comfort working in a fast-moving startup environment. Ability to collaborate across technical and business teams. Interest in AI, machine learning, automotive technology, and data-driven products #J-18808-Ljbffr Stealth Startup