Summary
✨ AI‑Generated
Join a data engineering team building reliable data solutions for complex supply-chain environments. You will work on data pipelines, data quality, analytics, and scalable data platforms while helping turn operational data into actionable business insights.
Highlights
Hybrid role with the opportunity to work on data engineering that supports complex supply chains, data quality, analytics, compliance, and business decision-making.
Description
Company Description
SourceDogg is a supply chain and procurement platform designed to turn supplier management into a profit-driving, risk-resilient advantage.
The platform delivers clean supplier data, automated compliance, streamlined sourcing, and predictive insights to help organizations improve tender cycles, reduce risk, and achieve significant cost savings.
SourceDogg serves procurement, supply chain, finance, and commercial teams across construction, manufacturing, pharmaceuticals, and other sectors with complex supply chains.
Its capabilities include supplier onboarding and qualification, data-led supplier performance management, proactive risk and compliance monitoring, and ESG and carbon reporting.
With SourceDogg, global enterprises and growing SMEs gain visibility into spend, risk, and supplier performance, enabling them to win more work and demonstrate total value.
Role Description
This full-time Data Engineer role is a hybrid position based in Londonderry, with flexibility for some work from home.
The Data Engineer will design, build, and maintain scalable data pipelines that support SourceDogg’s analytics, reporting, and product features.
Day-to-day responsibilities include developing and optimizing ETL processes, implementing robust data models and warehousing solutions, and ensuring data quality, integrity, and security across multiple data sources.
The role involves collaborating with product, engineering, and analytics teams to translate business requirements into technical solutions, supporting dashboards and insights used by customers and internal stakeholders.
The Data Engineer will also monitor system performance, troubleshoot issues, and contribute to continuous improvement of the data infrastructure.
Qualifications
Candidates should possess strong Data Engineering skills, including building and maintaining data pipelines and integrating multiple data sources.Candidates should possess Data Modeling skills focused on designing efficient, scalable schemas for analytics and operational workloads.Candidates should possess Extract Transform Load (ETL) skills for developing reliable, automated data ingestion and transformation workflows.Candidates should possess Data Warehousing skills for implementing and managing modern warehouse solutions and query optimization.Candidates should possess Data Analytics skills to support reporting, dashboards, and insight generation for internal and customer-facing use cases.Experience with SQL and at least one programming language commonly used in data engineering (e.g., Python, Scala, or Java).Familiarity with cloud data platforms and related services (e.g., AWS, Azure, or GCP) and modern data tools.Strong problem-solving abilities, attention to detail, and the capacity to work collaboratively in cross-functional teams.Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.Experience in supply chain, procurement, or enterprise SaaS environments is beneficial.
