Strategic Finance & Insights Analyst

City of London
8 months ago
Applications closed

Related Jobs

View all jobs

Python Data Engineer - Hedgefund

Head of DevOps and DataOps

Lead Data Engineer (Azure)

Lead Data Engineer / Architect – Databricks Active - SC Cleared

Senior Data Engineer x1/ Data Engineer x1 (Financial Services)

Data Governance Analyst

Job Title: Strategic Finance & Insights Analyst

Location: North East London

Department: Finance/Business Operations

Reports to: Chief Operating Officer

Employment Type: Part-Time, 3 days, Hybrid.

Role Summary

Burman Recruitment are seeking a highly analytical and strategic Finance & Insights Analyst to join our client. This role is ideal for someone who thrives at the intersection of finance, data, and strategy, someone who can scope complex work, analyse data, extract insights, assess funding sources, and drive performance improvement through meaningful metrics and financial reporting.

The successful candidate will support strategic planning and decision-making by delivering high-quality analysis and reporting, identifying areas for operational or financial improvement, and helping define key deliverables for business initiatives.

Key Responsibilities

  1. Work Scoping & Planning

    Collaborate with stakeholders to define the scope, objectives, and deliverables for strategic initiatives.

    Break down complex business problems into actionable workstreams.

  2. Data Analysis & Insight Generation

    Analyse financial and operational data to identify trends, risks, and opportunities.

    Use tools such as Excel, SQL, or BI platforms (Power BI/Tableau) to create meaningful insights.

    Translate findings into actionable recommendations and reports.

  3. Financial Reporting

    Prepare, maintain, and improve regular financial reports for leadership teams.

    Conduct variance analysis and explain key performance shifts.

    Ensure reporting is clear, accurate, and aligned with business goals.

  4. Strategic Deliverables

    Define and manage key deliverables across financial and business initiatives (e.g., business cases, dashboards, process improvements).

    Collaborate across departments to ensure timely delivery.

  5. Funding & Financial Source Assessment

    Identify and evaluate sources of funding, including internal budgets, grants, or external investments.

    Conduct ROI, cost-benefit, and break-even analysis to support strategic initiatives.

  6. Metrics & Performance Improvement

    Design and maintain KPIs aligned with business strategy.

    Monitor performance against targets and benchmarks.

    Proactively identify underperforming areas and suggest improvements.

    Key Skills & Experience

    Bachelor's degree in Finance, Business, Economics, Data Analytics, or related field.

    3+ years of experience in financial analysis, business strategy, or a related analytical role within Higher Education.

    Strong experience with Excel; proficiency in SQL and data visualisation tools (Power BI, Tableau) is a plus.

    Strong analytical and critical thinking skills.

    Excellent communication and data storytelling abilities.

    Comfortable working independently and cross-functionally in a fast-paced environment.

    Ability to calculate students per staff head count.
    Experience in strategic finance, corporate planning, or consulting.

    Knowledge of financial planning systems or tools (e.g. Adaptive Insights, Oracle, Agresso).

    Exposure to budgeting processes and cost analysis in large or complex organisations

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Maths for Data Engineering Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data engineering jobs in the UK, maths can feel like a vague requirement hiding behind phrases like “strong analytical skills”, “performance mindset” or “ability to reason about systems”. Most of the time, hiring managers are not looking for advanced theory. They want confidence with the handful of maths topics that show up in real pipelines: Rates, units & estimation (throughput, cost, latency, storage growth) Statistics for data quality & observability (distributions, percentiles, outliers, variance) Probability for streaming, sampling & approximate results (sketches like HyperLogLog++ & the logic behind false positives) Discrete maths for DAGs, partitioning & systems thinking (graphs, complexity, hashing) Optimisation intuition for SQL plans & Spark performance (joins, shuffles, partition strategy, “what is the bottleneck”) This article is written for UK job seekers targeting roles like Data Engineer, Analytics Engineer, Platform Data Engineer, Data Warehouse Engineer, Streaming Data Engineer or DataOps Engineer.

Neurodiversity in Data Engineering Careers: Turning Different Thinking into a Superpower

Every modern organisation runs on data – but without good data engineering, even the best dashboards & machine learning models are built on sand. Data engineers design the pipelines, platforms & tools that make data accurate, accessible & reliable. Those pipelines need people who can think in systems, spot patterns in messy logs, notice what others overlook & design elegant solutions to complex problems. That is exactly why data engineering can be such a strong fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a data engineering career, you might have heard comments like “you’re too disorganised for engineering”, “too literal for stakeholder work” or “too distracted for complex systems”. In reality, the traits that can make traditional office environments hard often line up beautifully with data engineering work. This guide is written for data engineering job seekers in the UK. We’ll cover: What neurodiversity means in a data engineering context How ADHD, autism & dyslexia strengths map to common data engineering tasks Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data engineering – & how to turn “different thinking” into a genuine professional superpower.

Data Engineering Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the data engineering jobs market in the UK is evolving fast. Almost every organisation is talking about AI, analytics & data-driven decision making – but behind all that sits the data engineering function. Cloud costs, complex data estates, stricter regulation & the explosion of AI workloads are all changing how data platforms are built & run. Some companies are tightening budgets & consolidating teams, while others are doubling down on modern data stacks, lakehouses & real-time pipelines. Whether you are a data engineering job seeker planning your next move, or a recruiter building data teams, understanding the key data engineering hiring trends for 2026 will help you stay ahead.