Allan GaigherData engineering & infrastructure
GitHub·LinkedIn

Selected work

A few projects that show how I work.

Details are anonymised but representative of the kind of problems I solve: migrations, reporting, and applied AI in financial and data-heavy environments.

Applied AI & AssistantsReporting & AnalyticsData Platforms & Pipelines

Applied AI & internal assistants

LLM-powered tools that sit inside a secure perimeter and automate the boring, error-prone parts of data and reporting work.

Reconciliation assistant for a mid-market asset manager

LLM assistant that guides ops through daily reconciliation.

Lead Data Engineer6 months
~3h → ~45min per day15+ users
Challenge

Operations teams spent hours each day stepping through spreadsheets and checks to reconcile positions and cash.

Solution

Built an internal LLM assistant that guides operations staff through daily reconciliation, using existing controls and playbooks.

Implementation
  • Ingested trade, position, and cash data into a governed warehouse.
  • Wrapped existing reconciliation logic with a conversational interface.
  • Added explanations and audit trails for every suggested action.
Impact

Reduced average reconciliation time per day from ~3 hours to ~45 minutes.

Regulatory Q&A bot for policy documents

Retrieval-augmented assistant over internal policy docs.

Data Engineer3 months
1000+ documents indexedDays → minutes to answer
Challenge

Analysts and compliance teams repeatedly asked the same policy questions, digging through PDFs and emails for answers.

Solution

Implemented a retrieval-backed assistant over internal policy documents to answer routine regulatory questions from analysts and compliance.

Implementation
  • Built document ingestion and chunking pipelines with metadata tagging.
  • Deployed a retrieval layer with strict access control by team and region.
  • Logged and reviewed prompts/answers to tune relevance and safety.
Impact

Cut time-to-answer for common policy questions from days to minutes.

Reporting & analytics (Power BI, Tableau)

Dashboards and semantic models that answer real questions for finance, risk, and operations — not just vanity metrics.

Executive performance dashboards for a PE-backed fintech

Board-ready Power BI model for recurring performance reporting.

Lead Data Engineer4 months
Single trusted modelWeekly exec & board use
Challenge

Leadership relied on inconsistent spreadsheets for ARR, churn, and unit economics.

Solution

Designed and delivered a Power BI model used by the exec team for weekly performance and board reporting.

Implementation
  • Modelled ARR, churn, and unit economics from multiple source systems.
  • Implemented row-level security for finance, sales, and operations.
  • Documented KPI definitions so finance and product spoke the same language.
Impact

Replaced a collection of spreadsheets with a single, trusted source of truth.

Front-office analytics for a trading desk

Low-latency P&L and limits dashboards for traders and risk.

Data Engineerongoing
Intraday refreshesAlerts on limit breaches
Challenge

Traders and risk teams had fragmented views of P&L, exposure, and limits across tools.

Solution

Built low-latency dashboards to monitor daily P&L, risk, and limits with intraday refreshes.

Implementation
  • Designed a warehouse model optimised for fast slice-and-dice queries.
  • Added alerting on rule breaches directly into the reporting layer.
  • Worked with desk heads to simplify layouts to what they actually used.
Impact

Improved visibility and reduced time spent reconciling numbers between teams.

End-to-end data platforms & pipelines

Data platforms that collect, clean, and serve data reliably — often in regulated or audit-heavy environments.

Cloud migration of a legacy reporting stack

Migrated on-prem reporting stack to a modern cloud data platform.

Lead Data Engineer9 months
Zero-downtime cutoverAll key reports migrated
Challenge

Critical reporting ran on ageing on-prem SQL and Excel workflows that were hard to change and fragile.

Solution

Led the migration from on-prem SQL and Excel workflows to a modern cloud data platform.

Implementation
  • Designed the target architecture on Azure with managed services.
  • Ran dual-running period with automated reconciliation between old and new stacks.
  • Trained the internal team to own and extend the platform after go-live.
Impact

Achieved zero-downtime cutover and simplified future change requests.

Data platform for a multi-strategy fund

Central platform feeding risk, finance, and front-office reporting.

Data Engineer12 months
Shared data modelFewer reconciliation issues
Challenge

Different teams maintained their own data extracts and definitions for core measures.

Solution

Helped design and build a central platform feeding risk, finance, and front-office reporting.

Implementation
  • Implemented ingestion patterns for market, reference, and trade data.
  • Collaborated with risk and finance to align data definitions and controls.
  • Set up monitoring so teams saw issues before auditors did.
Impact

Improved confidence in firm-wide reporting and reduced fire-fighting around month-end.