We're transforming our customer support data from static, disconnected reports into a live, AI-powered system. We're looking for an experienced Data Engineer to build the pipelines, storage, and logic that power our new AI agents — turning messy customer chats and tickets into clean, structured information our AI can reliably use.

Job Responsibilities
Ingest and clean large volumes of unstructured support data from Bliss, Salesforce, Sprinklr, and JIRA
Design storage and retrieval systems (including vector databases) that give our AI accurate, relevant context
Build a centralized, reliable metrics layer for AI-driven analytics
Build robust, monitored, failure-resistant pipelines — no fire drills
Partner with ops, product, and engineering; push back on poor data practices at the source

Required Skills




5+ years in data engineering with big data tools (Hadoop, Hudi, Spark, Presto, Pinot, Flink, Kafka) and cloud data warehouses
Strong hands-on Python and PySpark
Proven use of AI tools (e.g., Claude, Codex) to accelerate development — automating checks, parsing messy text, building data logic layers
Direct experience with vector databases (Pinecone, Milvus, Weaviate, pgvector) and AI-feeding data pipelines
Bonus: experience building metric or semantic layers

If this prospect aligns with your experience and interests, I'd be happy to discuss it further. Please send your updated resume to [email protected] .

📌 Mid/Senior Data Engineer (Vasanthanagar)
🏢 Pegasus Knowledge Solutions
📍 Vasanthanagar