Senior Data Engineer

Janus Henderson is hiring a Senior Data Engineer to set technical direction for a subsystem or cross-product concern within the Janus Henderson Data Platform. The role focuses on designing resilient, production-grade data products and platform capabilities across multiple domains, including applied AI tooling when appropriate. Key Responsibilities Own the design and delivery of complex data engineering capabilities across subsystems or cross-product concerns, including setting technical direction within the role’s 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 across query-plan, pipeline, and platform levels. Assess architectural trade-offs, including build-versus-buy choices and second-order effects on 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 guardrails for a regulated environment. Own quality gates, observability, and incident learning for the scope of work, including postmortems, root cause analysis, and continuous improvement actions. Mentor junior engineers and data engineers, run design reviews, and establish standards that others can apply consistently. Communicate technical trade-offs clearly to architecture, product, operations, compliance, and other non-technical stakeholders. Collaborate on source code through DevOps practices, including deep understanding of branching strategies and releasing production-quality code through change control processes. Carry out other duties as assigned. Required Qualifications 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 optimization, 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 spanning 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 DevOps experience, including branching strategies, and familiarity with 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, including the ability to understand hand-offs between Investments, Distribution, Operations, Regulatory, Corporate, and Finance processes. Ability to write clear design documentation and present trade-offs to non-technical stakeholders while influencing engineering standards beyond the immediate product area. Experience with production-grade AI-enabled tooling, including 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. Technologies SQL Python Snowflake dbt Orchestration CDC/streaming MCP tooling, MCP servers Agents, retrieval pipelines, RAG/retrieval pipelines Azure Portal, Keyvault, Appreg Azure Data Factory Azure DevOps CI/CD vscode copilot Benefits Hybrid working and reasonable accommodations Generous Holiday policies Excellent Health and Wellbeing benefits including corporate membership to Wellhub Paid volunteer time to step away from your desk and into the community Support to grow through professional development courses, tuition/qualification reimbursement, and more Maternal/patal leave benefits and family services Unique employee events and programs including a 14er challenge Complimentary beverages, snacks, and all employee Happy Hours Annual Bonus Opportunity (annual discretionary bonus award from the profit pool, funded based on Company profits) 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. Supervisory Responsibilities No supervisory responsibilities. Potential for Growth Mentoring Leadership development programs Regular training Career development services Continuing education courses Compensation and Application Details Location: Denver, CO (hybrid) Salary: USD 140,000 - 149,000 per year (base salary range estimated for the role; actual pay may differ). Posting availability: This position will be open through October 15, 2026. Colorado law requires an estimated closing date for job postings. If you see this date has passed, you are still encouraged to apply. #J-18808-Ljbffr Janus Henderson