Data Engineer
Summary
Builds and optimizes large-scale data pipelines and search systems using Python, Spark, and SQL, with a focus on indexing, relevance tuning, and knowledge graphs.
Ideally 5+ years of experience as a Data Engineer, including exposure to large scale or Big Data environments
Strong experience with SQL and database systems (relational and NoSQL), including query optimization and schema design
Hands on experience with search platforms or information retrieval technologies (indexing, ranking, text search, semantic search, metadata modeling, vector search, relevance tuning, etc.)
Knowledge of Graph Databases (e.g., Neo4j, Cosmos DB Gremlin API) and their application to knowledge graphs or entity relationship search
Strong programming skills in Python, Scala, Spark, and experience with Big Data tools such as Azure Cloud, Databricks, and PowerBI (or equivalents)
Experience designing or maintaining search APIs, indexing pipelines, or metadata driven search components
Good understanding of Agile methodologies and experience delivering incrementally within an Agile team
Strong communication and stakeholder management skills, with the ability to translate search related needs into technical solutions
Solid analytical, problem solving, and data management abilities
Proactive team player with flexibility, resilience, and the initiative to drive improvements across search and data discovery workflows
Strong interest in understanding business context to create meaningful and effective data search experiences
Fluent in English with excellent written and verbal communication skills, and the ability to work as part of a global team