Ink Search Ltd
Front Office Tech Lead - Data Intelligence Platform. Global Commodity Trader
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Company Description
At the heart of global supply, our client connects vital resources to power and build the world. Through Oil & Petroleum Products, Gas and Power, and Metals and Minerals, they use infrastructure, logistics, and financing to connect producers and consumers to make supply more efficient, secure, and sustainable. They are accelerating investments in renewable energy, including hydrogen, ammonia, and other low-carbon energy technologies required for the transition to a low carbon future.
A career within this client offers a gateway to working on some of the most exciting challenges of a rapidly changing world – from helping to optimise supply chains to developing infrastructure and new markets. Everyone has a voice and is empowered to collaborate across geographies and disciplines to help shape our business and the wider world. We know the importance and value of diversity in our business and we invest in attracting, developing, and retaining talent from all backgrounds.
Role Description
Group Technology is delivering a Cloud Smart, Data First strategy: a multi-year programme to consolidate fragmented data across the firm's eTRMs, risk, finance, operations, and asset systems into a connected, enterprise-grade data backbone. Enterprise Data's flagship expression of that strategy is the Intelligence Platform: the Lakehouse, semantic layer, catalogue, streaming backbone, and AI/agent enablement capabilities set out in the Data Architecture target-state.
This role is the technical delivery owner for the Intelligence Platform end-to-end, being the person who turns the target architecture, design principles, and capability roadmap into a working, production-grade platform. The role reports to the Head of Data, and is accountable for engineering the Databricks/AWS substrate, the lakehouse (Iceberg/Delta), streaming and CDC pipelines, the semantic and knowledge-graph layer, and the AI/agent enablement surface (governed retrieval, MCP gateway, agent identity).
This is a hands-on, build-it role as much as a lead-it role. The successful candidate will have personally built a comparable data/AI platform before, not just directed one, and will bring that experience to bear leading a team of internal technology leads while directing the work of multiple external vendors and delivery partners (systems integrators, Databricks/AWS partners, specialist tooling vendors) to a single coherent architecture and delivery plan.
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In the near term, the role stands up the Databricks/AWS substrate, lands the first certified data products, builds the streaming backbone and semantic/knowledge-graph layer, and establishes the engineering standards and SDLC that let domain teams ship products without a platform engineer in the room.
Key Responsibilities
Platform architecture & hands-on delivery
- Execution of the technical build of the Intelligence Platform end-to-end: lakehouse (Databricks/AWS, Iceberg/Delta), semantic layer, catalogue/lineage, streaming backbone, storage & lifecycle, and AI/agent enablement
- Engineer and review the platform's foundational components: ingestion, transformation, semantic modelling, streaming, where hands-on delivery moves faster than delegation
- Guide and enforce engineering standards: CI/CD, environment parity, code review, testing, and observability
Streaming, AI, and knowledge graph enablement
- Build and operate the streaming backbone (Kafka/Kinesis/Flink, CDC) as a first-class capability, not an afterthought to batch ingestion.
- Participate in the design & delivery of the Enterprise Knowledge Graph and the semantic/context layer as production data products.
- Deliver the AI & Agent Enablement band, governed retrieval, MCP gateway, and tool registry, agent identity, and action controls in partnership with AI Enablement.
Team and vendor leadership
- Lead and develop a team of internal technology leads, setting technical direction, unblocking delivery, and building bench strength.
- Direct the work of multiple external vendors and delivery partners, systems integrators, Databricks/AWS specialists, and point-solution vendors, holding them to a single architecture, a shared delivery plan, and defined engineering standards.
Delivery management & governance
- Own the technical delivery plan and roadmap for the Intelligence Platform
- Track and report delivery progress, technical risk, and vendor performance
Qualifications
- Significant hands-on experience architecting and building enterprise-scale data/AI platforms, including prior experience personally leading the build of a comparable hybrid cloud/on-prem platform from the ground up.
- Deep technical fluency across AWS and Databricks (or directly comparable lakehouse platforms), including Unity Catalog, Delta/Iceberg, DLT/streaming, and serverless compute.
- Direct experience building and operating streaming/CDC pipelines (Kafka, Kinesis, Flink, or equivalent) at production scale.
- Practical experience with ClickHouse or comparable low-latency/OLAP serving technology.
- Experience designing and building Knowledge Graphs (e.g. Neo4j, Stardog, or equivalent) and integrating them with AI/agentic retrieval patterns.
- Proven track record establishing robust SDLC practice, CI/CD, GitOps/infrastructure-as-code, environment parity, testing, and code review discipline, across a multi-team delivery organisation.
- Track record leading technical teams and directing third-party vendors/SIs to a shared delivery outcome.
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Preferred Qualifications
- Experience in commodities trading, energy, or financial services, with familiarity with eTRM platforms and trading data domains (trade, position, P&L, exposure, curves).
- Hands-on experience with AI/agentic frameworks (e.g. MCP, LangGraph, Databricks Agent Framework) and governed retrieval/RAG patterns.
- Experience with open table formats (Iceberg/Delta) and multi-engine lakehouse architectures.
- Familiarity with data governance, catalogue, and lineage tooling (e.g. Unity Catalog, DataHub, OpenLineage) and how engineering choices support certification and compliance gates.
- Operating in a federated/Data Mesh delivery model, enabling domain teams to self-serve on a shared platform.
Attributes to Success
- Builder first: wants to be in the architecture and the code, not just the roadmap slide, and is credible in a design review down to schema, pipeline, and reliability detail.
- Comfortable being the technical anchor across multiple vendors simultaneously.
- Pragmatic under delivery pressure: sequences a multi-year target architecture into shippable, evidenced increments.
- Strong mentor and developer of technical leads, builds a team that outlasts any single delivery phase.
- Forward-looking on AI, knowledge graphs, and the evolving data platform landscape, translating emerging capability into governed, durable engineering rather than point experiments.
This is a really exciting opportunity and requires a "best in class" Technical Lead with a strong pedigree in trading-oriented data platform architecture and delivery.
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