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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** JANUS HENDERSON GLBL - **Location:** Denver, CO, United States - **Experience:** Expert - **Salary:** $140,000.0 - $149,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, DevOps, Distributed Computing Environment, Distributed Data Store, Python (Programming Language), Key Management, Performance Tuning, Cloud Services, Data Streaming, Subsystems, Macros, Azure Data Factory, Sql Optimization, Large Language Models, Snowflake, Data Layers, Git Flow, Software Version Control, Databricks - **Published:** September 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=53a8bc44a3274005 ## About the Role * Deep expertise in at least one data platform pillar, such as Snowflake internals, dbt architecture, orchestration, CDC/streaming or distributed data processing. * Advanced SQL skills, including query-plan analysis, performance tuning, cost optimisation and troubleshooting on cloud data platforms. * Strong Python engineering capability, with experience building reusable frameworks, packages or libraries rather than only one-off scripts. * Proven ability to design systems that span multiple products, domains or platform concerns, with awareness of downstream impacts and operational risk. * Experience making technical trade-offs under delivery pressure, including scope, quality, build-versus-buy and maintainability decisions. * Strong experiences with DevOps, branching strategies, Azure Portal/Keyvault/Appreg concept. * Experience with Microsoft Azure services, such as Azure Data Factory, Azure Key Vault and Azure DevOps, for CI/CD and infrastructure integration. * Working knowledge of financial services data domains, with the ability to understand hand-offs between Investments, Distribution, Operations, Regulatory, Corporate and Finance processes. * Ability to write clear design documentation, present trade-offs to non-technical stakeholders and influence engineering standards beyond your immediate product area. * Experience with production-grade AI-enabled tooling, such as agents, RAG/retrieval pipelines, MCP servers or AI-assisted engineering workflows. * Must be able to use vscode copilot for development work * Experience mentoring engineers, leading design reviews and supporting technical decision-making across a team or guild. Nice to have skills * Experience with dbt Core/Cloud, including custom macros, packages, tests, contracts or materialisations. * Experience designing or operating semantic layers, entitlement engines, concordance models, data contracts or reusable platform services. * Understanding of AI/LLM risk in a regulated environment, including data egress, auditability, model non-determinism and appropriate guardrails. * Knowledge of data governance frameworks, lineage tooling, Data Mesh principles and distributed data ownership. * Certifications or demonstrable advanced capability in Snowflake, Databricks, dbt or equivalent cloud data platform technologies. ## Description As a Senior Data Engineer, you will own the technical direction for a subsystem or cross-product concern within the Janus Henderson Data Platform. You will act as a go-to engineer for architectural decisions in your area, designing resilient data products and platform capabilities that span multiple business domains. The role requires deep technical craft, strong domain awareness, applied AI fluency, and the ability to influence engineering standards across the Data Engineering guild. * Own design and delivery of complex data engineering capabilities across subsystems or cross-product concerns, setting technical direction within your area. * Design systems that span multiple products or domains, such as entitlement models, concordance frameworks, semantic layers, ingestion frameworks or reusable platform services. * Provide deep technical expertise in at least one core platform pillar, including Snowflake internals, dbt architecture, orchestration, CDC/streaming or equivalent platform capabilities. * Build reusable engineering assets, including dbt macros, custom materialisations, Python packages, ingestion frameworks, MCP tooling or other shared libraries where the standard toolkit does not fit. * Diagnose and resolve performance, reliability and cost issues at query-plan, pipeline and platform level. * Assess architectural trade-offs, including build-versus-buy decisions and second-order impacts across downstream reporting, analytics, operations and regulatory processes. * Design and deliver production-grade AI-enabled tooling where appropriate, including agents, retrieval pipelines, MCP servers or other applied AI capabilities with appropriate guardrails for a regulated environment. * Own quality gates, observability and incident learning for your area, including postmortems, root cause analysis and continuous improvement actions. * Mentor junior engineers and data engineers, run design reviews and establish standards that other engineers can adopt consistently. * Communicate technical trade-offs clearly to architecture, product, operations, compliance and other non-technical stakeholders. * DevOps and Source Control Work with fellow team members to collaborate and review source code. Deep understanding of branching strategies and able to release production quality code through change control processes. * Carry out other duties as assigned, * Mentoring * Leadership development programs * Regular training * Career development services * Continuing education courses Compensation information The base salary range for this position is $140,000 - $149,000. This range is estimated for this role. Actual pay may be different. This position will be open through October 15, 2026. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Why Git Still Matters](https://www.wearedevelopers.com/videos/100288-why-git-still-matters) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)