Data Analyst/Business Intelligence Specialist

IMI plc

We are a global specialist engineering company that creates breakthrough solutions. We are curious and like to solve problems, partnering with our customers to solve the demands of today and prepare for the challenges of tomorrow. We embrace innovation and care about outcomes that are good for business, everyday life and making a better world – creating lasting impact for everyone.

We design, build and service highly engineered products in fluid and motion control applications. We focus on five market sectors: Industrial Automation, Process Automation, Climate Control, Life Science and Fluid Control, and Transport.

Climate Control offers hydraulic solutions for water-based heating and cooling systems to achieve a perfect indoor climate with minimal energy consumption. Our leading brands have been used in over 100,000 building projects worldwide and offer products and solutions in three key areas: Pressure maintenance and water quality, regulation, control and actuators, and thermostatic control.

Role Overview

The Data Analyst will support the Data and Business Intelligence Manager in developing and implementing data strategies, driving analytics transformation, and ensuring the integrity and security of company data. This role involves analyzing business data, providing actionable insights, and supporting data-driven decision-making processes.

Key Responsibilities

·   Collect, clean, and analyze data from various internal and external sources to support data-driven decision-making and business objectives.

·   Develop, maintain, and optimize dashboards and reports to monitor key performance indicators (KPIs) and business metrics, ensuring clarity and relevance for stakeholders.

·   Assist in the design, configuration, and maintenance of BI tools and data infrastructure, including databases, data pipelines, and visualization tools (e.g., Power BI, Tableau, etc.).

·   Collaborate with cross-functional teams to identify data requirements, trends, and opportunities for business improvement, providing actionable insights based on data analysis.

·   Ensure data accuracy, consistency, and integrity by performing data quality checks and validation, creating clear documentation for tracking and troubleshooting.

·   Conduct in-depth and ad-hoc analysis using statistical methods and advanced analytics to answer specific business questions and uncover hidden trends.

·   Drive the promotion of data literacy and a data-driven mindset across departments, conduct training sessions and fostering a culture of data-backed decision-making.

·   Support predictive analytics and business intelligence initiatives by designing and delivering reports that focus on forecasting and advanced analytics to deliver real business value.

·   Collaborate with IT and data engineering teams to ensure data pipelines and integrations are efficient, scalable, and well-documented for continuous data flow and availability.

·   Responsible for end-to-end testing of business reports and dashboards, ensuring data accuracy, performance, and user satisfaction before reports are distributed to stakeholders.

Qualifications

Education: Bachelor’s degree in Data Science, Statistics, Computer Science, Finance or a related field.

Experience: Proven experience as a Data Analyst or in a similar role.

Skills: 

·   Excellent verbal and written communication skills to present findings in a clear and engaging manner.

·   Skilled in extracting and analyzing data to derive meaningful business insights.

·   Proficiency in PowerPoint to create compelling presentations that effectively communicate data-driven insights.

·   Strong understanding of business operations and strategy to contextualize data insights.

·   Ability to distill complex information into clear, concise, and actionable recommendations.

·   Ability to work independently and as part of a team.

·   Commitment to data accuracy and integrity.

·   Strong analytical and problem-solving skills.

·   Proficiency in data analysis tools such as SQL, Excel, and data visualization tools (e.g., Tableau, Power BI).

·   Experience with programming languages such as Python or R.

·   Knowledge of database management and data warehousing concepts.

·   Familiarity with machine learning techniques and algorithms.

·   Experience with cloud-based BI solutions (AWS or Azure).