Data Engineer

1 week ago

bangalore, India OWOW Full time

Data Engineer – AI-Powered Marketing Personalization PlatformWe're seeking an experienced Data Engineer to help build and scale our next-generation AI-powered marketing personalization platform (V2.0). You'll design and implement a robust multi-database infrastructure that enables real-time personalization, vector search, graph analytics, and large-scale data processing.This is a greenfield opportunity to architect data pipelines from the ground up using vector and graph databases and LLM-based systems. You'll play a key role in migrating our existing platform while creating a scalable foundation powering AI agents across thousands of marketing campaigns.Core ResponsibilitiesData Architecture & Infrastructure (40%)Design and implement multi-database systems (MongoDB, Redis, Milvus, Neo4j, BigQuery)Build scalable real-time pipelines and ETL/ELT workflowsImplement data governance, quality, and high-throughput optimizationVector & Graph Systems (25%)Optimize Milvus collections for semantic searchDesign Neo4j schemas for customer journeys and relationshipsDevelop hybrid search (vector + graph + text) with performance tuningML Data Infrastructure (20%)Build data pipelines for LLM fine-tuning and GNN trainingManage data versioning, lineage, and A/B testing systemsImplement real-time feature computation for contextual modelsAnalytics & Monitoring (15%)Create BigQuery schemas and real-time dashboardsImplement observability (Prometheus, Grafana) and anomaly detectionOptimize data costs across cloud environmentsTech StackDatabases: MongoDB, Redis, Milvus, Neo4j, BigQuery Processing: Airflow/Prefect, Pandas/Polars, dbt, Spark ML Pipeline: vLLM, MLflow, Sentence Transformers, PyTorch, TensorFlow Cloud & Infra: GCP, Docker, Kubernetes, Terraform, GitHub Actions Languages: Python (3.10+), SQL, BashRequirementsMust-Have5+ years of data engineering experience in production systemsAdvanced Python and SQL expertiseExperience with 3+ database types (SQL, NoSQL, Vector, Graph)Proven ability to build high-scale data pipelines (>1M records/day)Strong data modeling, validation, and optimization skillsExperience with cloud data warehouses (BigQuery, Redshift, or Snowflake)PreferredExperience with Milvus, Pinecone, or WeaviateGraph databases (Neo4j, Neptune) and embedding-based searchML/Feature store experienceBackground in marketing technology or CDPsKey ProjectsPhase 1 – Foundation: Migrate 10M+ vectors, implement MongoDB schemas, Neo4j models, and BigQuery warehouse Phase 2 – Optimization: Build data quality monitoring, caching (Redis), and

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