SourceDogg
Data Engineer

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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:
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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- Developing and optimizing ETL processes
- Implementing robust data models and warehousing solutions
- Ensuring data quality, integrity, and security across multiple data sources
- Collaborating with product, engineering, and analytics teams to translate business requirements into technical solutions
- Supporting dashboards and insights used by customers and internal stakeholders
- Monitoring system performance, troubleshooting issues, and contributing to continuous improvement of the data infrastructure


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Qualifications
- Strong Data Engineering skills, including building and maintaining data pipelines and integrating multiple data sources
- Data Modeling skills focused on designing efficient, scalable schemas for analytics and operational workloads
- Extract Transform Load (ETL) skills for developing reliable, automated data ingestion and transformation workflows
- Data Warehousing skills for implementing and managing modern warehouse solutions and query optimization
- 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
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