Data Analyst

Data Analyst job in Manchester – DOE

The Opportunity

Interact is looking for a highly analytical Data Analyst to join the business and play a key role in understanding and optimising commercial and financial performance. This is a hands-on position suited to someone who enjoys working directly with large datasets, investigating issues at record level, and building trusted analytical outputs that inform strategic business decisions.

Unlike traditional reporting-focused analyst positions, this role requires deep engagement with data across multiple business systems. You will work across millions of records, validating, reconciling, sampling, and analysing information from sales, marketing, finance, and operational platforms to create an accurate and reliable view of business performance.

The organisation already has established reporting frameworks, metrics, and commercial funnels in place. Your role will involve maintaining and refining these existing structures while also conducting exploratory analysis to uncover new trends, identify opportunities, test assumptions, and generate valuable business insights.

Working closely with the CEO, CFO, executive leadership team, and private equity stakeholders, you will transform complex business questions into robust analytical outputs and automated reporting solutions that support confident decision-making.

Key Responsibilities

Marketing and Sales Funnel Analysis

• Analyse large-scale marketing and sales datasets across platforms including HubSpot, Salesforce, and web analytics tools.
• Investigate individual records to identify inconsistencies, duplicate entries, and data quality issues.
• Build automated analytical workflows using SQL and Python to aggregate, clean, and transform data.
• Identify gaps in data collection, integration, and reporting processes across multiple systems.
• Conduct exploratory analysis to uncover new trends, patterns, and growth opportunities.
• Maintain accurate and trusted reporting across the full customer acquisition and sales funnel.

Financial and Revenue Analysis

• Analyse Annual Recurring Revenue (ARR), Monthly Recurring Revenue (MRR), customer churn, revenue growth, and profitability metrics.
• Assess customer lifecycle movements and monitor the overall ARR growth trajectory.
• Reconcile data across multiple business systems, including Salesforce, Sage, and proprietary invoicing platforms.
• Produce accurate financial analysis to support business planning and investor reporting requirements.
• Connect product usage metrics with commercial outcomes such as customer retention, expansion, contraction, and churn.
• Support strategic decision-making through detailed financial and operational analysis.

Data Engineering and Automation

• Develop and maintain automated reporting processes and data pipelines using Python, SQL, and related technologies.
• Build scalable data workflows that improve efficiency and reduce manual reporting effort.
• Implement automated reconciliation processes and data quality controls across systems.
• Create well-documented scripts, processes, and analytical frameworks that improve reliability and consistency.

Stakeholder Engagement

• Work directly with executive leadership teams, including the CEO, CFO, and wider board members.
• Collaborate with private equity stakeholders to deliver accurate, investor-grade reporting and analysis.
• Translate complex business requirements into structured analytical approaches and actionable insights.
• Present findings clearly and confidently to senior business and financial stakeholders.
• Support the development of data literacy across the organisation through effective communication and reporting.

Operational and Cross-Functional Support

• Partner with Operations and Customer Success teams to support forecasting, capacity planning, and process optimisation.
• Perform root-cause investigations into operational challenges and business performance issues.
• Work closely with Product and Engineering teams to ensure data structures and reporting models align with business requirements.
• Contribute to continuous improvement initiatives across commercial, financial, and operational functions.

Skills and Experience

The ideal candidate will have a strong analytical background combined with experience working with SaaS business metrics and complex commercial datasets.

Essential Requirements

• Experience working with SaaS performance metrics, including ARR, MRR, churn, pipeline management, conversion funnels, and unit economics.
• Proven ability to reconcile and validate data across multiple systems, including CRM, finance, invoicing, and marketing platforms.
• Strong attention to detail and commitment to data accuracy.
• Ability to work independently and deliver analysis that senior stakeholders can rely on with confidence.
• Excellent communication skills with experience presenting findings to executive-level audiences.
• Collaborative approach with the confidence to work closely with senior leaders across multiple business functions.
• Strong academic background, ideally in a quantitative discipline such as Mathematics, Statistics, Economics, Engineering, Computer Science, or a related field.

Desirable Experience

• Previous experience within a private equity-backed SaaS organisation.
• Knowledge of investor reporting and board-level reporting requirements.
• Experience using data visualisation platforms such as Power BI, Tableau, or Looker.
• Understanding of ETL processes, data warehousing, and data modelling concepts.
• Experience working with Salesforce, HubSpot, Sage, or comparable business systems.
• Familiarity with forecasting, operational performance metrics, customer health monitoring, and capacity planning.

This is an excellent opportunity for a commercially focused Data Analyst to work at the heart of a growing SaaS business, delivering high-impact analysis that directly influences strategic decision-making, operational performance, and long-term business growth.