On-site
Part Time
● Design and implement a multi-database architecture (MongoDB, Redis, Milvus, Neo4j, BigQuery)
● Build scalable data pipelines for real-time conversation processing and personalization
● Architect ETL/ELT workflows for data migration from legacy systems
● Implement data partitioning, sharding, and optimization strategies for high-throughput systems
● Design and optimize Milvus vector collections for semantic search (1024-dim embeddings)
● Build graph schemas in Neo4j for customer journey mapping and persona relationships
● Implement HNSW indexing strategies and similarity search optimization
● Create hybrid search systems combining vector, full-text, and graph queries
● Monitor and tune database performance (query latency, throughput, resource utilization)
● Build data collection pipelines for LLM fine-tuning (conversation logs, tool executions)
● Create feature stores for GNN training (customer interactions, engagement signals)
● Implement data versioning and lineage tracking for ML experiments
● Design A/B testing data infrastructure with CUPED variance reduction
● Build real-time feature computation pipelines for contextual bandits
● Design BigQuery schemas for marketing analytics and performance tracking
● Create materialized views and aggregation pipelines for real-time dashboards
● Implement data quality monitoring and anomaly detection
● Build observability infrastructure (Prometheus metrics, Grafana dashboards)
● Develop cost optimization strategies for cloud data warehousing
● Migrate 10M+ conversation vectors from Pinecone to Milvus
● Design and implement MongoDB schemas for real-time agent state
● Set up Neo4j graph database with customer journey models
● Create BigQuery data warehouse with partitioned tables
● Build automated data quality monitoring system
● Implement caching strategies (Redis) for 10x latency reduction
● Optimize vector search queries (target: <50ms p95 latency)
● Create real-time analytics dashboards (Grafana)
● Build LLM fine-tuning data pipeline
● Implement feature store for GNN training
● Create A/B testing data infrastructure
● Design multi-armed bandit state management
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