C&D Foods and its affiliates are one of the largest pet food manufacturers in Europe, offering specially formulated cat and dog food for the private label market. Founded in 1969, C&D Foods and its affiliates have grown to become one of the industry's leading pet food producers with eight manufacturing sites across Europe supplying quality products to customers around the world. We provide a one-stop-shop for all our customer's wet and dry pet food needs, from large-scale, low-cost highly automated facilities to multi-purpose, smaller volume flexible sites. Through our dedicated Nutrition & Research Centre and focus on continuous improvement, we've developed a reputation for innovation, collaboration, quality and market expertise.
As a Data Engineer within the Group IT team, you will have a breadth and depth of experience and technical ability to support the continued development and evolution of our data and analytics capabilities within a fast-paced food manufacturing environment. Previous experience delivering data engineering solutions within a manufacturing industry setting would be beneficial, enabling you to understand the complexities of production, quality supply chain and operational data.C&D Foods has grown through acquisition and as such we have a varied data landscape and architecture. This role will be responsible for designing, building, and maintaining robust data solutions that are fit for purpose today but also with an eye to our future needs and ambitions for growth.
The purpose of this role will be to transform operational and business data into trusted, high-quality datasets, dashboards, semantic models, and automated workflows that improve performance, visibility, and decision-making across the organisation. A core part of the role is dedicated to data preparation and cleansing, including profiling, standardisation, enrichment, API-based integration support, and ongoing data quality monitoring.
The ideal candidate will possess strong SQL and data warehousing expertise, coupled with hands-on experience across modern database, data engineering, data analysis, reporting, semantic modelling, BI and workflow automation platforms. This includes Microsoft technologies such as Power BI, Power Query, DAX and Power Automate, while also being adaptable to broader enterprise platforms used across cloud, on-premise and hybrid data environments.
Personal Attributes
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Strong analytical and problem-solving skills.
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Excellent attention to detail and commitment to data accuracy.
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Ability to communicate technical concepts effectively to non-technical stakeholders.
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Strong organisational and prioritisation skills.
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Self-motivated with a continuous improvement mindset.
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Ability to work independently and collaboratively across multiple departments.
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Ability to work with ambiguity and competing priorities.
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Demonstrable stakeholder management, communications and interpersonal skills.
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Ability to quickly learn new technologies and new products.
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Excellent written and verbal communication skills, strong presentation skills.
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Passion for technology and solving for business needs.
Qualifications
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Degree in Computer Science, Information Technology, Data Analytics, Software Engineering, or a related discipline.
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Relevant Microsoft certifications in Power BI, Azure Data Engineering, Microsoft Fabric, or SQL technologies would be advantageous.
Technical Skills
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Strong SQL development skills with experience writing and maintaining complex queries, stored procedures, views, and database objects.
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Excellent understanding of relational database concepts and SQL fundamentals.
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Experience with relational and analytical database platforms including SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, Databricks, Google BigQuery, Amazon Redshift, or equivalent technologies.
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Ability to work across cloud, on-premise, and hybrid data platforms, adapting data engineering approaches to the technology landscape in place.
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Understanding of modern data platform concepts, including data lakes, lakehouses, warehouses, marts, semantic layers, APIs, batch processing, and near real-time data integration.
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Solid understanding of dimensional modelling and data warehouse concepts.
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Experience developing and supporting ETL/ELT and data integration solutions using tools such as SSIS, Azure Data Factory, dbt, Airflow, Informatica, Talend, Matillion, Fivetran, or equivalent platforms.
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Ability to evaluate and apply appropriate data preparation, transformation, and integration techniques using SQL, low-code, no-code, cloud-native, or code-based tooling as required.
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Experience with data preparation, cleansing, profiling, transformation, API-based integration, validation, and data quality management.
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Proven experience developing Power BI dashboards and reports.
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Experience or ability to work with a range of business intelligence, reporting, and analytics platforms such as Power BI, Tableau, Qlik, Looker, Cognos, SSRS, or equivalent tools.
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Strong understanding of reporting design principles, governed datasets, reusable metrics, self-service analytics, and stakeholder-focused visualisation regardless of reporting platform.
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Strong experience with Power Query (M) and DAX.
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Experience creating and maintaining semantic models and reporting datasets.
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Knowledge of data quality validation, data governance, and data management principles.
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Experience with Microsoft Power Automate for workflow and business process automation.
Desirable Skills
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Experience in a food manufacturing, FMCG, or production environment.
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Knowledge of ERP systems, Manufacturing Execution Systems (MES), supply chain, or quality management systems.
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Experience with Microsoft Fabric, Azure, AWS, Google Cloud Platform, Snowflake, Databricks, or equivalent modern data platforms.
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Exposure to analytical tools such as Excel Power Query, Alteryx, Python, R, notebooks, or similar tooling.
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Knowledge of data governance, security, metadata management, API integrations, and Power Platform administration.
Data Engineering & Data Management
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Design, develop, and maintain data pipelines and curated datasets to support business reporting and analytics.
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Develop and maintain SQL code, including complex queries, stored procedures, views, functions, and database objects.
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Support the extraction, transformation, and loading (ETL) of data from SQL Server, Oracle, ERP systems, manufacturing platforms, and other business applications.
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Monitor, troubleshoot, and optimise database performance, data integration processes, and data quality.
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Ensure data accuracy, integrity, consistency, and availability across reporting and analytics solutions.
Data Preparation & Cleansing
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Carry out data profiling, cleansing, standardisation, and transformation activities to improve data quality and suitability for reporting and analytics.
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Prepare and structure operational data from ERP, manufacturing, quality, supply chain, finance, and third-party systems into reusable curated datasets.
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Support API-based data integration, including the extraction, preparation, validation, and transformation of data across internal and external platforms.
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Develop repeatable data preparation rules, transformation logic, and cleansing processes to support reporting and analytics solutions.
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Monitor and improve data quality through validation checks, reconciliation routines, exception reporting, and stakeholder engagement.
Data Warehouse & Modelling
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Support the design, implementation, and maintenance of enterprise data warehouse solutions.
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Develop and maintain dimensional models using recognised data warehousing methodologies.
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Create and optimise semantic models and reporting datasets to support self-service reporting and advanced analytics.
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Build and maintain star schemas, fact tables, dimensions, and business reporting structures.
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Enhance data models, semantic layers, and calculation frameworks to improve reporting performance and usability.
Power BI Development & Business Intelligence
- Design, develop, and maintain interactive Power BI dashboards, reports, scorecards, and semantic models for operational and strategic decision-making.
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Develop and maintain Power Query and DAX solutions, including measures, calculated columns, and advanced analytical calculations.
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Create intuitive visualisations that communicate complex data insights to business stakeholders.
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Collaborate with business users to translate reporting requirements into scalable solutions while ensuring best practices for performance, governance, security, and usability.
Process Automation & Continuous Improvement
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Automate business processes and workflows using Microsoft Power Automate.
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Identify opportunities to improve operational efficiency through automation, data integration, and streamlined reporting processes.
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Support digital transformation initiatives through collaboration with stakeholders and the implementation of low-code automation solutions.
Data Quality, Governance & Documentation
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Implement data quality validation, reconciliation processes, exception monitoring, and continuous improvement initiatives across manufacturing and business systems.
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Develop and maintain technical documentation for data pipelines, business rules, data models, and reporting solutions.
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Support organisational data governance standards and best practices.
