Janus Henderson is hiring a Senior Data Engineer to help shape the technical direction for a subsystem or cross-product area within the Janus Henderson Data Platform. In this hybrid role in Denver, CO, you will design production-grade data products and platform capabilities across multiple domains, including applied AI-enabled tooling where appropriate.
Key Responsibilities
- Own the 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 capabilities.
- Build reusable engineering assets, including dbt macros, custom materialisations, Python packages, ingestion frameworks, MCP tooling, or other shared libraries when standard tooling does not fit.
- Diagnose and resolve performance, reliability, and cost issues across query-plans, pipelines, and the platform.
- Assess architectural trade-offs such as build-versus-buy and second-order downstream effects on 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 scope, including postmortems, root cause analysis, and continuous improvement actions.
- Mentor junior engineers and data engineers, run design reviews, and establish standards other engineers can adopt consistently.
- Communicate technical trade-offs clearly to architecture, product, operations, compliance, and other non-technical stakeholders.
- Work with team members to collaborate on and review source code, including strong understanding of branching strategies and releasing production-quality code through change control processes.
- Carry out other duties as assigned.
Requirements
- 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, including experience creating reusable frameworks, packages, or libraries rather than only one-off scripts.
- 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, covering scope, quality, build-versus-buy, and maintainability decisions.
- Strong experiences with DevOps and branching strategies, including 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 understanding 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.
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 Key Vault, 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.
Growth and Development
- Mentoring
- Leadership development programs
- Regular training
- Career development services
- Continuing education courses
Compensation and Timing
- Base salary range: $140,000 - $149,000 per year (estimated for this role; actual pay may differ).
- This position will be open through October 15, 2026.
- Colorado law requires an estimated closing date for job postings; applying after the listed date is not discouraged.
