Back
Mid-level generalist data engineer with common stack and metro/remote appeal increases competition.
Specific CRM/ERP and tooling experience required, yet core data engineering skills remain transferable across industries.
Multiple mandatory platform and tooling requirements (Salesforce, Siebel, Oracle, Hadoop, Spark) increase filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own end-to-end construction, deployment, and maintenance of scalable data pipelines integrating Salesforce, Siebel CRM, Oracle ERP, SQL Server, and Azure Cloud data sources.
Lead data quality initiatives including profiling and automated validation to ensure data accuracy and compliance across core RevOps and GTM systems.
Collaborate with cross-functional teams to align data engineering efforts with business analytics and reporting needs, enhancing marketing, sales, and customer support data workflows.
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Applied Mathematics, or related technical field.
5+ years of progressive experience in data engineering with enterprise-scale data ecosystems involving CRM, ERP, and cloud systems.
Proficiency in SQL and big data frameworks such as Hadoop and Spark; hands-on experience with Salesforce, Siebel CRM, Oracle ERP, and cloud data integration.
Working hours aligned to UK business hours.
Strong background in multi-system data pipeline design and maintenance within CRM and ERP environments, with a strategic understanding of marketing and sales automation platforms.
Experienced in implementing data quality frameworks and automated testing to support data governance and AI/ML readiness.
Comfortable working in fast-paced, cross-functional settings requiring collaboration with technical teams and business stakeholders to deliver scalable data solutions.