Data Analytics Compliance Analyst, Infiltration

Severn Trent Water; Coventry; On-site; GBP 42,000 - 62,000; Full time

Benefits offered by this job

25 days holiday + bank holidays (and买)

Annual bonus scheme (up to £1500)

Leading pension scheme - double your 7

Sharesave – discounted Severn Trent股份

Dedicated training and development

Electric vehicle scheme and retail》

Family friendly policies

Two volunteering days per year

Job summary

Severn Trent Water is seeking a Compliance Analyst on the Infiltration programme at our head office in Coventry, with occasional travel to our Derby office. You will help identify, understand and reduce infiltration into the wastewater network, developing data platforms, dashboards and analytics to enable multi-million-pound investment decisions.

You will work with Senior Analysts to transform data usage, support strategic monitoring, and deliver predictive models while ensuring data quality and

Qualifications

• Strong data analysis skills and experience with large, complex datasets.
• Proficiency in SQL, Python and BI tools.
• Background in engineering, environmental science or related field preferred.

Responsibilities

• Develop and maintain the programme's data platforms and dashboards.
• Support data, monitoring and analytics projects to inform investment decisions.
• Create the Infiltration Dashboard for diverse stakeholders from field teams to senior leaders.

Skills

Data analysis

Analytical mindset

Problem solving

Education

Quantitative degree

Tools

SQL

Python

Power BI

Tableau

Qlik

Job description

Severn Trent Water is seeking a Compliance Analyst on the Infiltration programme at our head office in Coventry, with occasional travel to our Derby office. You will help identify, understand and reduce infiltration into the wastewater network, developing data platforms, dashboards and analytics to enable multi-million-pound investment decisions.

You will work with Senior Analysts to transform data usage, support strategic monitoring, and deliver predictive models while ensuring data quality and