Malvern Panalytical
Data Engineer
Remote Senior Data Engineer role with clear candidate location fit.
PostedJul 18, 2026
Eligible countries43 accepted countries
Seniority signalSenior
Work settingRemote
Accepted candidate locations
Role overview
Data Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
Key Responsibilities:
- Data Architecture & Pipeline Engineering: Architect, build, and operate resilient data pipelines integrating Salesforce, SAP, and service data into highly governed analytical and operational data products. Lead the technical implementation utilizing Microsoft Fabric, Dataverse, Python, and SQL.
- AI Context Management: Design and own the context layer for AI agents. Deliver curated, versioned data products with strict data contracts, entity resolution, and optimized retrieval interfaces to ground LLM/AI outputs.
- Intelligent Feedback Loops: Establish sophisticated feedback systems to capture agent outcomes, human corrections, and downstream results, seamlessly feeding them back into data products, prioritization models, and scoring logic.
- Advanced Reporting & Analytics: Oversee the delivery of robust Power BI dashboards, semantic models, and datasets covering critical agent performance, pipeline/funnel metrics, and data quality.
- Data Quality, Governance & Security: Set the standards for and implement robust data-quality frameworks (completeness monitoring, deduplication, entity resolution, and source reconciliation). Define and enforce data lineage, access controls, retention, and compliance protocols in close partnership with IT and data owners.
- Integration Evolution: Drive the modernization of our data landscape by transitioning legacy, file/export-based flows toward secure, modern, API-based, in-perimeter integration patterns.
Role Requirements
- Experience & Autonomy: 6+ years of hands-on data engineering experience, with a proven track record of owning end-to-end data architectures and production pipelines supporting operational (not just analytical) enterprise use cases.
- Technical Stack Expertise: Deep expertise across the Microsoft data stack (Fabric, Dataverse, Power BI) alongside advanced Python and SQL development skills.
- Integration Expertise: Proven experience integrating complex enterprise data from Salesforce and/or SAP, specifically utilizing modern API-based integration patterns.
- Advanced AI Data Engineering: Direct experience designing data modeling/entity resolution frameworks across CRM/ERP domains, as well as designing context/retrieval layers (e.g., RAG systems) and feedback loops for AI/LLM applications.
- Leadership & Stewardship: Proven ability to make independent architectural and tooling decisions, set technical standards for engineering teams, and ensure the absolute reliability of data feeding customer-facing AI agents.
Leadership Behaviours.
- Inspire Your People: Communicate a compelling technical vision, simplify complex architectural challenges, and plan for the long-term interest of the business. Bring positive energy, ambition, high integrity, and a proactive willingness to learn from setbacks.
- Strengthen Your Team: Set a high bar for technical excellence, hold peers and collaborators accountable, and foster a growth mindset through coaching, mentoring, and active collaboration.
- Grow Your Business: Implement data strategies that deliver tangible business results. Put customers at the heart of what you build, proactively optimize existing processes, and champion the Spectris Business Systems.
Company Values
- Own It: We believe in teamwork, keeping promises, and building our brands together.
- Aim High: We choose to be bold and positive to perform at our best and achieve greater success.
- Be True: We act with absolute integrity to win for our stakeholders, the environment, and our colleagues.
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