Lead Data Solutions Architect

Job Description

As Lead Data Solutions Architect, you will shape how Frontline’s products use data end to end — from how information is captured, through how it flows via pipelines and orchestration, to how it supports insight, automation, and decision‑making in live products.

Data and analytics are central to the role, but it is not a narrow “data‑only” position. You will design complete solutions, thinking across products, integrations, data platforms, and intelligent workflows.

You will report directly to the Technology Director and work closely with the Head of Engineering & Platform. Engineering owns delivery and runtime behaviour; you own solution design, data architecture, orchestration patterns, and applied intelligence, staying close enough to the build to ensure designs work in practice. As our Lead Data Architect, you will be expected to design, build, and iterate.

You’ll be responsible for

• Designing end‑to‑end data‑led and intelligence‑driven solutions across Frontline’s products, from application data capture through pipelines, orchestration, analytics, and downstream actions.
• Hands‑on design and build of data pipelines, including ingestion, transformation, modelling, and consumption, ensuring data is reliable, well‑structured, and usable in live systems.
• Designing and implementing data orchestration and workflow patterns that coordinate pipelines, services, analytics, and automated actions reliably in production.
• Building and evolving agent‑style, workflow‑driven solutions where data, rules, models, and services work together to automate decisions or guide users inside products, with a strong focus on control, explainability, and robustness.
• Shaping solution designs that bring together applications, data platforms, analytics, orchestration, and integrations, rather than treating intelligence as a separate layer.
• Producing clear, lightweight solution designs that describe data flow, storage choices, analytics patterns, orchestration logic, and integration points, with a focus on simplicity and long‑term maintainability.
• Working directly with modern data platforms, including Snowflake and Microsoft Fabric (or equivalent), and SQL‑based data stores, to prototype, implement, and evolve data and analytics solutions.
• Helping teams make pragmatic design decisions around performance, scalability, reliability, and cost, based on how products are actually used in production.
• Defining and promoting practical data quality, modelling, and orchestration practices, ensuring solutions are trusted and reusable without introducing heavy governance.
• Working closely with engineers and product‑mindful teams to translate business problems into buildable pipelines, orchestrations, and intelligent behaviours.
• Designing integration patterns where data and decisions need to flow cleanly between products, supporting platforms, and external systems.
• Supporting other engineers through hands‑on collaboration, review, and problem‑solving, rather than architecture boards or document‑heavy processes.

Frontline operates in a .NET‑based environment, with cloud‑hosted platforms and modern Dev Ops tooling.

On the data side, we use modern data platform architectures, including:

• cloud data warehouses and lakehouse‑style approaches
• platforms such as Snowflake and Microsoft Fabric
• SQL‑based data modelling
• orchestrated pipelines and workflows embedded directly into products

You don’t need to be a specialist in every tool, but you do need to be comfortable building and owning data pipelines, orchestration logic, and intelligent workflows that can run confidently in production.

• Hands‑on experience designing and building modern data architectures, including data warehouse, lakehouse, and end‑to‑end data platform patterns.
• Strong experience with cloud‑based analytical platforms such as Snowflake or equivalent modern data platforms (e.g. Fabric, Databricks), and understanding where they fit within a wider solution.
• Practical experience designing and implementing data pipelines, covering ingestion, transformation, modelling, and consumption using SQL‑first and cloud‑native…