Technical Business Analyst

Primus Connect; Slough; Hybrid; GBP 66,000 - 111,000; Full time

Job summary

Primus Connect is seeking a highly analytical Source System Analyst/Technical Business Analyst for an Insurance Data Transformation Programme in London.

You will investigate unfamiliar source systems, profile data with SQL, and translate findings into evidence for downstream design teams. This hybrid role starts ASAP, runs long-term through Sep 2027, with a day rate of £550–£600.

Qualifications

• Insurance domain experience and concepts.
• Strong SQL proficiency for data profiling and validation.
• Experience with complex data estates and unfamiliar source systems.
• Technical data analysis and data modelling awareness.
• Technical business analysis and translating conversations into technical investigations.

Responsibilities

• Investigate unfamiliar insurance source systems and databases.
• Use SQL to interrogate complex data estates and validate assumptions.
• Identify where key insurance entities are represented within source systems.
• Understand how data entities relate to one another and their history.
• Produce SQL queries to support findings and assist mapping/design teams.
• Document assumptions, findings and source-system behaviour.

Skills

Insurance domain experience

SQL proficiency

Technical data analysis

Data modelling awareness

Technical business analysis

Tools

SQL

Job description

Technical Business Analyst - Insurance Data Transformation Programme

Start: ASAP / September 2026

Duration: Long-term contract, expected to run through to approximately September 2027

Rate: £550/day target, with flexibility up to £600/day for the right person

Location: Hybrid – London approximately 1 day per week, particularly during onboarding

The Programme

We are supporting a major insurance organisation through a large-scale data transformation and legacy re-platforming programme.

At the heart of the programme is the creation of a standardised enterprise data model designed to provide a consistent view of insurance data across areas including policy, claims, reinsurance and other core insurance domains.

The programme is working across a complex estate of approximately 25 source systems. These systems vary significantly in structure, terminology, documentation and data quality.

The architecture follows a broadly Medallion-style approach, with data moving from legacy source systems through raw/bronze layers and into a standardised, conformed enterprise model.

The programme initially operated with a single delivery squad while the architecture, data model and ways of working were established. It is now moving into a scale phase, growing to multiple parallel delivery squads.

The Role

We are looking for a highly analytical and technically capable Source System Analyst/Technical Business Analyst to join the programme.

This is not a conventional Business Analyst position. The role sits somewhere between a Technical Business Analyst, Data Analyst and Source System SME, with a strong emphasis on hands-on investigation of data.

You will be responsible for understanding unfamiliar insurance source systems and identifying where the data required by the target model actually sits, how it behaves and how different entities relate to one another.

Some source systems may contain hundreds or even thousands of tables, with limited documentation and limited retained knowledge within the business.

Your role is to carry out the initial investigation and provide the downstream Data Designers with enough understanding to move into detailed mapping and solution design.

Key Responsibilities

• Investigate unfamiliar insurance source systems and databases.
• Use SQL to interrogate complex and potentially poorly documented data estates.
• Identify where key insurance entities and business concepts are represented within source systems.
• Understand how data entities relate to one another.
• Reduce large numbers of source tables down to the subset relevant to a particular requirement.
• Analyse how data behaves over time, including history, overwrites, effective dates and record lifecycle.
• Work with business SMEs and system owners to understand the purpose and behaviour of source data.
• Continue investigations independently where documentation or SME knowledge is incomplete.
• Read and interpret target data models.
• Carry out source-to-target analysis.
• Produce SQL queries to support and evidence findings.
• Document assumptions, findings and source-system behaviour.
• Provide Data Designers with sufficient analysis to begin detailed solution design.
• Work closely with Data Designers and Data Engineers throughout delivery.
• Support multiple delivery squads as the programme continues to scale.

Essential Experience

• Insurance Domain Experience - You should have a strong understanding of insurance data and common insurance concepts.
• Experience across multiple insurance organisations or source systems would be particularly valuable.
• Strong SQL - You must be comfortable working directly with data using SQL.

You should be able to use SQL to, profile data, understand table structures, identify relationships, validate assumptions, investigate data behaviour etc

• Technical Data Analysis - You should have strong experience analysing complex data environments and working through unfamiliar systems.
• Technical Business Analysis - You should be able to work effectively with business stakeholders and SMEs, understand requirements and translate those conversations into technical data investigations.
• Data Modelling Awareness

The ideal person is naturally curious, technically capable and comfortable solving problems where the answer isn't immediately available.

If documentation doesn't provide the answer and the SME doesn't know, you need to be the type of person who gets into the data and works it out.

We're looking for someone who can independently get the team 80–90% of the way towards understanding a source system, rather than someone who waits for every question to be answered before progressing.

If you enjoy getting into complex data, understanding how systems really work and translating that knowledge into something a delivery team can act on.