Sr Data Engineer

What you'll do

• Design and build high-performance streaming and batch data pipelines for AI applications.
• Implement embedding generation workflows and vector store integrations to support semantic search and AI assistants.
• Develop scalable storage solutions that are cost-efficient and perform well in production.
• Integrate data pipelines with shared AI platform services to ensure reliable data delivery.
• Embed observability into data systems, including metrics, logging, alerts, and failure analysis.
• Mentor junior team members and lead by example through high-quality code and proactive problem solving.

What we're looking for

• 5+ years of data engineering experience with at least 1 year in a lead or senior technical role.
• Expertise in building and scaling streaming data pipelines in large-scale, distributed environments using tools like Kafka, Flink, Spark, Kinesis.
• Proficiency in Python, Java, and SQL, with advanced skills in either Python or Java.
• Experience with embedding pipelines and vector stores such as Pinecone, Weaviate, FAISS, pgvector.
• Strong knowledge of data modeling, storage optimization, and retrieval patterns for large-scale systems.
• Hands-on experience with workflow orchestration tools like Airflow, Dagster.
• Proven ability to collaborate closely across AI engineering, infrastructure, product teams.