Top Benefits
About the role
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Graph focused) based in Canada. This is a highly hands-on, evaluation-driven engineering role focused on building and benchmarking enterprise-scale knowledge graph solutions. You will work at the intersection of data engineering, graph technologies, and database performance analysis to determine the most effective architecture for large-scale knowledge systems. The environment is experimental and deeply technical, requiring structured testing across multiple database technologies under controlled conditions. You will design and execute repeatable benchmarks to compare graph databases against relational approaches like PostgreSQL. The role demands strong engineering rigor, as decisions are based on measurable performance, not assumptions or opinions. You will collaborate with architecture and engineering stakeholders to translate results into actionable recommendations. This is an opportunity to influence foundational data infrastructure decisions in a high-impact, enterprise context. \n
Accountabilities: In this role, you will be responsible for designing, building, and executing structured evaluations of graph and relational database technologies to support enterprise architecture decisions. Extract and process datasets from Databricks, transforming them into graph-ready models for benchmarking across multiple database systems Deploy, configure, and repeatedly spin up/down graph database environments such as Neo4j and TigerGraph, ensuring controlled and reproducible test conditions Design and implement relationship models and entity linkages that accurately represent production-grade knowledge graphs Develop benchmark queries using graph query languages (e.g., Cypher, GSQL, nGQL, AQL, openCypher) and compare against PostgreSQL recursive CTE baselines Build APIs and testing layers to evaluate real-world query performance across different usage scenarios and workloads Produce structured analysis, scoring frameworks, and technical documentation to support final architecture recommendations Requirements: We are looking for a highly technical data engineer with strong experience in databases, benchmarking, and graph data modeling, combined with a structured and analytical mindset. Strong hands-on experience in data engineering, ideally with Databricks or equivalent large-scale data platforms Proven experience with at least two graph database technologies, with strong preference for Neo4j and/or TigerGraph Advanced PostgreSQL expertise, including recursive CTEs, query planning, indexing strategies, and materialized views Solid understanding of graph query languages such as Cypher and experience translating relational logic into graph traversal patterns Demonstrated ability to design and execute structured performance benchmarks in enterprise environments Comfort working in iterative, experimental setups where databases are frequently deployed, tested, and decommissioned Bonus: experience in KYC/AML data environments, Kubernetes-based database workloads, or AWS-managed database infrastructure Strong analytical thinking, communication skills, and ability to present technical findings to engineering and architecture stakeholders Benefits: Competitive compensation aligned with senior-level expertise and market standards in Canada Flexible hybrid working model, with preference for Toronto-based collaboration 15 days of annual vacation (pro rata) 10 paid sick days per year (non pro rata) Access to structured onboarding support and buddy system during initial weeks Learning and development support, including training, certifications, and technical growth opportunities Exposure to global enterprise clients across multiple industries Inclusive, collaborative culture focused on autonomy and ownership Regular team events, office perks, and community initiatives (including breakfasts, lunches, and snacks in office locations) Opportunity to contribute to socially responsible initiatives through company-wide volunteer programs.
\n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1
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Top Benefits
About the role
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Graph focused) based in Canada. This is a highly hands-on, evaluation-driven engineering role focused on building and benchmarking enterprise-scale knowledge graph solutions. You will work at the intersection of data engineering, graph technologies, and database performance analysis to determine the most effective architecture for large-scale knowledge systems. The environment is experimental and deeply technical, requiring structured testing across multiple database technologies under controlled conditions. You will design and execute repeatable benchmarks to compare graph databases against relational approaches like PostgreSQL. The role demands strong engineering rigor, as decisions are based on measurable performance, not assumptions or opinions. You will collaborate with architecture and engineering stakeholders to translate results into actionable recommendations. This is an opportunity to influence foundational data infrastructure decisions in a high-impact, enterprise context. \n
Accountabilities: In this role, you will be responsible for designing, building, and executing structured evaluations of graph and relational database technologies to support enterprise architecture decisions. Extract and process datasets from Databricks, transforming them into graph-ready models for benchmarking across multiple database systems Deploy, configure, and repeatedly spin up/down graph database environments such as Neo4j and TigerGraph, ensuring controlled and reproducible test conditions Design and implement relationship models and entity linkages that accurately represent production-grade knowledge graphs Develop benchmark queries using graph query languages (e.g., Cypher, GSQL, nGQL, AQL, openCypher) and compare against PostgreSQL recursive CTE baselines Build APIs and testing layers to evaluate real-world query performance across different usage scenarios and workloads Produce structured analysis, scoring frameworks, and technical documentation to support final architecture recommendations Requirements: We are looking for a highly technical data engineer with strong experience in databases, benchmarking, and graph data modeling, combined with a structured and analytical mindset. Strong hands-on experience in data engineering, ideally with Databricks or equivalent large-scale data platforms Proven experience with at least two graph database technologies, with strong preference for Neo4j and/or TigerGraph Advanced PostgreSQL expertise, including recursive CTEs, query planning, indexing strategies, and materialized views Solid understanding of graph query languages such as Cypher and experience translating relational logic into graph traversal patterns Demonstrated ability to design and execute structured performance benchmarks in enterprise environments Comfort working in iterative, experimental setups where databases are frequently deployed, tested, and decommissioned Bonus: experience in KYC/AML data environments, Kubernetes-based database workloads, or AWS-managed database infrastructure Strong analytical thinking, communication skills, and ability to present technical findings to engineering and architecture stakeholders Benefits: Competitive compensation aligned with senior-level expertise and market standards in Canada Flexible hybrid working model, with preference for Toronto-based collaboration 15 days of annual vacation (pro rata) 10 paid sick days per year (non pro rata) Access to structured onboarding support and buddy system during initial weeks Learning and development support, including training, certifications, and technical growth opportunities Exposure to global enterprise clients across multiple industries Inclusive, collaborative culture focused on autonomy and ownership Regular team events, office perks, and community initiatives (including breakfasts, lunches, and snacks in office locations) Opportunity to contribute to socially responsible initiatives through company-wide volunteer programs.
\n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1