Senior Database Engineer

About Neo4j: Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems. It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world’s largest graph community. Intelligence that works. Results that matter. Built to work everywhere and integrate with everything across every cloud for dynamic, personalized, and autonomous AI systems. We deliver quicker results, contextual knowledge, and solutions that impact customers and employees across the business. Our Vision:  At Neo4j, we have always strived to help the world make sense of data.   As business, society and knowledge become increasingly connected, our technology promotes innovation by helping organizations to find and understand data relationships. We created, drive and lead the graph database category, and we’re disrupting how organizations leverage their data to innovate and stay competitive. THE ROLE Join the team behind Neo4j Graph Analytics for Snowflake, our Snowflake Native App that brings the full power of Neo4j Graph Data Science directly into customers' Snowflake accounts, with no data movement required. You'll work on a product that lives natively inside Snowflake: a containerized Java + Python runtime, a SQL-first API, and a release pipeline that ships graph analytics to enterprise data platforms. Our customers are data engineers and data scientists across financial services, supply chain, telco, and beyond, who use it to run PageRank, community detection, pathfinding, and node embeddings against the warehouses where their data already lives. This is a hands-on, mid-to-senior role at the intersection of graph analytics, cloud-native distribution, and DevOps, with a meaningful say in the platform's technical direction. WHAT YOU'LL DO * Build and evolve the Neo4j Graph Analytics for Snowflake application, embedding Neo4j Graph Data Science into the Snowflake platform. * Design and improve our SQL-facing API: stored procedures, UDFs, and the surface area customers call from their warehouses. * Own significant parts of the build, release, and deployment pipeline: Snowflake CLI, Gradle, container images, and the Java/Python runtimes that execute inside Snowpark Container Services. * Improve the platform's security posture: caller's rights vs. owner's rights stored procedures, restricted caller's rights (RCR), grants, and proactive image scanning. * Collaborate with customers and Solution Engineers to turn real-world requirements into scalable features. * Contribute to operational excellence: runbooks, release processes, observability, and reproducible dev environments. WHAT YOU'LL BRING * 4+ years of professional experience building and shipping production-quality software. * Strong SQL skills and real experience integrating with cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks, or similar). * Solid grounding in at least one of Java or Python, and willingness to be effective in both. * A genuine DevOps mindset: comfortable owning build pipelines, container images, releases, and the operational side of a product. * Experience designing software for performance, scalability, and predictable cost on cloud infrastructure. BONUS POINTS * Hands-on experience with Snowflake, especially Native Apps, Snowpark Container Services, or building stored procedures and UDFs at scale. * Familiarity with Docker, OCI image registries, and security scanning tooling (Semgrep, Snyk, Trivy, etc.). * Understanding of graph theory and graph algorithms (centrality, community detection, pathfinding, embeddings), or strong curiosity to learn them. * Background in distributed systems, JVM performance tuning, or columnar/analytical query engines. Experience working in a distributed, remote-first team and shipping to enterprise customers. #Li-Hybrid Why Join Neo4j? Neo4j is, without question, the most popular graph intelligence platform in the world. We have customers in every industry globally, and our products are a proven product/market fit. Joining our team is an opportunity to shape the future of data and analytics. Below are just a few exciting facts about Neo4j.  * Neo4j is one of the fastest-scaling technology companies in this industry. It recently surpassed $200M in annual recurring revenue (ARR), doubling its ARR over the past three years.  * Raised the biggest funding round in database history ($325M Series F). Backed by world-class investors like Eurazeo, GV (formerly Google Ventures), and Inovia Capital, Neo4j has raised over $600M in funding and is currently valued at over $2Bn. This puts Neo4j among the most well-funded database companies in history. * 84% of the Fortune 100 and 58% of the Fortune 500 use Neo4j. Examples include Boston Scientific, BT Group, Caterpillar, Cisco, Comcast, Department for Education UK, eBay, NBC News, Novo Nordisk, Worldline, and others.  * Co-founder and CEO Emil Eifrem has built an amazing culture that prides itself on relationships, inclusiveness, innovation, and customer success. * Countless industry awards. Massive enterprises and individual developers/data scientists love Neo4j. A strong sense of community and ecosystem is built around the platform. * A recent Forrester Total Economic Impact™ Study cited Neo4j as delivering 417% ROI to customers.  Research shows that members of underrepresented communities are less likely to apply for jobs when they don’t meet all the qualifications. If this is part of the reason you hesitate to apply, we’d encourage you to reconsider and give us the opportunity to review your application. At Neo4j, we are committed to building awareness and helping to improve these issues.  One of our central objectives is to provide an inclusive, diverse, and equitable workplace for everyone to develop their potential and have a positive, career-defining experience. We look forward to receiving your application. Neo4j Values: Neo4j is a Silicon Valley company with a Swedish soul. We foster collaboration and each of us is empowered to contribute and put our innovative stamp on projects. We hire candidates who reflect the following Neo4j core values: (we)-[:VALUE]->(relationships) (we)-[:FOCUS_ON]->(userSuccess) (we)-[:THRIVE_IN]->(:Culture {type: [‘Open’, ‘Inclusive’]}) (we)-[:ASSUME]->(:Intent {direction:’Positive’}) (we)-[:WELCOME]->(:Discussions {nature: ‘IntellectuallyHonest’}) (we)-[:DELIVER_ON]->(ourCommitments)  Neo4j is committed to protecting and respecting your privacy. Please read the privacy notice regarding Neo4j's recruitment process to understand how we will handle the personal data that you provide.  More information at www.neo4j.com.   ©2026 Neo4j, Inc., Neo Technology®, Neo4j®, Cypher®, Neo4j Bloom™, Neo4j Graph Data Science Library™, Neo4j® Aura™, and Neo4j® AuraDB™ are registered trademarks or a trademark of Neo4j, Inc. All other marks are owned by their respective companies.

ABOUT AIVIQ Aiviq is a cutting-edge fintech company revolutionising financial services and asset management. We empower the world's leading asset managers with data-driven insights and innovative technology solutions. Our cloud-based platform transforms complex financial data into actionable intelligence, addressing critical challenges in client data quality and insights. Serving global asset managers overseeing trillions in Assets under Management, we're at the forefront of financial technology innovation. Reporting Structure Reports to: Data Centre of Excellence Team Lead Dotted line to: Head of Engineering Location: UK (Hybrid) Job Purpose We're seeking an accomplished Data Engineer to join our Data Centre of Excellence while working closely with our Engineering team on our sophisticated financial data management platform. This role combines the technical depth of enterprise data engineering with the fast-paced delivery demands of product development, requiring someone who is adept at translating business logic into code, can think architecturally while attending to implementation details. You'll be the bridge between our data architecture standards and practical product delivery, ensuring our financial data pipelines are robust, performant, and built on solid engineering principles. Key Responsibilities Data Engineering & Development * Design, build, and optimize data pipelines across Microsoft SQL Server and Azure Synapse Analytics environments * Develop and maintain Spark SQL notebooks for complex data transformations and analysis * Translate business logic and financial calculation requirements into clear, maintainable code * Create data integrity checking scripts and validation frameworks in collaboration with QA teams * Implement automated data quality checks and reconciliation processes * Assist with the maintenance of a curated, anonymized dataset for system testing that covers all known scenarios and edge cases * Analyse production datasets to identify anomalies, debug stored procedures and notebooks, and resolve data quality issues * Demonstrate tenacity in investigating root causes, diving deep into complex problems until resolution is achieved Architecture & Performance * Consult on database architecture decisions, balancing performance, scalability, and maintainability * Optimize query performance and data processing workflows for large-scale financial datasets * Design and implement solutions using Azure Data Factory, Delta Lake, and related technologies * Think end-to-end about data flows while ensuring rigorous attention to implementation details Documentation & Process * Create and maintain comprehensive documentation of database schemas, processes, and data flows * Develop visual process models using tools such as Lucidchart, Visio, dbt, Azure Purview, or similar platforms * Document data transformation logic and calculation methodologies for audit and compliance purposes * Contribute to data governance standards and best practices across the organization Production Support & Collaboration * Act as first point of escalation for high-priority data issues in production environments * Partner with test automation engineers to develop data-driven testing strategies and create data integrity checking scripts * Collaborate across engineering teams using Azure DevOps for CI/CD pipeline development * Support both Data CoE initiatives and product engineering priorities through effective stakeholder management Required Skills & Experience Technical Expertise * Database Technologies: Strong proficiency in MS SQL Server and Azure Synapse Analytics * Big Data Processing: Hands-on experience with PySpark, Spark SQL, and notebook-based development * Cloud Platforms: Demonstrable experience with Azure ecosystem (Synapse, Data Factory, Delta Lake) * Programming: Solid coding skills in SQL, Python, and/or C# * Version Control: Experience with Git and Azure DevOps or similar CI/CD platforms * Testing: Experience building out unit and integration test frameworks and processes to ensure pipelines and notebooks and other code artefacts are fully automation-tested Domain Knowledge * Ideally a proven track record working with complex financial data and calculations * Understanding of financial data structures, reconciliation processes, and audit requirements * Experience handling temporal data, slowly changing dimensions, and historical data management * Knowledge of data quality frameworks and validation methodologies Professional Capabilities * Strong analytical and debugging skills for complex data scenarios across stored procedures and notebooks * Relentless problem-solving approach - comfortable digging deep into technical issues and pursuing answers until problems are fully understood and resolved * Experience with testing principles and data integrity validation * Ability to consult on technical architecture while maintaining pragmatic focus * Excellent documentation and process modelling capabilities Experience Level * 5+ years in data engineering roles with increasing responsibility * Track record of delivering production data systems at scale * Experience working in matrix or cross-functional team structures Desirable Skills * Knowledge of Azure Purview or data cataloguing solutions * Familiarity with Great Expectations or similar data quality frameworks * Understanding of behaviour-driven development for data testing * Familiarity with data anonymization, masking, and synthetic data generation techniques * Experience with GraphQL APIs and modern application data layers * Exposure to modern data visualization tools (Power BI, Tableau) * Experience with data build tool (dbt) or similar transformation frameworks Personal Attributes Essential * Collaborative mindset: Comfortable working across teams with different priorities and technical backgrounds * Detail-oriented: Meticulous about data accuracy while maintaining delivery momentum * Investigative nature: Thrives on troubleshooting complex issues and pursuing problems through multiple layers until fully resolved * Intensely curious: Demonstrates deep curiosity about existing processes and systems, with a natural drive to investigate how things work and independently acquire new knowledge * Pragmatic problem-solver: Balances architectural thinking with practical implementation * Clear communicator: Articulates technical concepts to both specialist and generalist audiences * Ownership mentality: Takes responsibility for production systems and follows through on commitments Cultural Fit * Thrives in a matrix organization with multiple stakeholders * Comfortable with ambiguity and competing priorities * Passionate about engineering excellence and continuous improvement * Values documentation and knowledge sharing * Responds well under pressure during production incidents What We Offer Professional Development * Exposure to enterprise-scale financial data systems handling complex calculations * Opportunity to shape data engineering standards across the organization * Work with modern Azure cloud infrastructure and emerging technologies * Collaborate with skilled engineers across test automation, software development, and data teams * Matrix structure providing diverse learning opportunities from both CoE and product perspectives Work Environment * Hybrid working arrangement with flexibility * Collaborative engineering culture valuing quality and craftsmanship * Investment in tools, training, and professional growth * Meaningful work on systems that impact financial data integrity and business decisions