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Metro location and mid-level experience increase competition, but niche graph specialization and smaller employer reduce it.
Graph specialization increases domain bias, but core Python/SQL data engineering skills remain transferable across industries.
Explicit 3+ years and mandatory Python/SQL skills make filters moderately strict.
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Design, develop, and maintain scalable graph data pipelines, integration workflows, and graph data models for complex business relationships.
Develop and optimize Python-based data ingestion, transformation, validation processes, and SQL queries for high-volume datasets to support analytical workloads.
Collaborate with cross-functional teams to translate data requirements into scalable graph database solutions and troubleshoot production issues for performance and reliability.
Minimum 3 years of experience in data engineering, database development, or graph database implementations.
Strong proficiency in Python for data engineering, automation, and backend processing.
Expertise in SQL including complex queries, optimization, and performance tuning.
Bachelor's or Master's degree in Computer Science, IT, Data Engineering, or related field.
Experienced in designing scalable, high-performance data systems and data pipelines primarily using Python and SQL.
Prior exposure to graph databases (e.g., Amazon Neptune, TigerGraph, Neo4j) and graph query languages is advantageous.
Comfortable working in Agile environments and collaborating with software engineers, data scientists, and product teams.