Data Engineer (Profisee MDM)

Next Ventures; United Kingdom; On-site; GBP 40,000 - 70,000; Full time

Job summary

A leading company is seeking a Data Engineer to design, integrate, and deliver data solutions that support enterprise systems. The role involves building structured data models, integrating systems, and engineering scalable data pipelines to ensure accurate data flow across platforms.

Qualifications

• Experience with Profisee MDM and ETL/ELT tools.
• Strong understanding of data modeling techniques and data integration strategies.
• Ability to design scalable data pipelines for enterprise systems.

Responsibilities

• Design and implement logical and physical data models.
• Create comprehensive data maps and define transformation logic.
• Design robust ETL/ELT pipelines for data ingestion.

Skills

Data Modeling

Data Integration

ETL Processes

Data Quality

Data Mapping

Job description

The Data Engineer is responsible for the end-to-end design, integration, and delivery of data solutions that support enterprise systems and business operations. Utilising Profisee MDM this role focuses on building structured data models, integrating disparate systems, and engineering scalable pipelines to ensure accurate and timely data flow across platforms.

1. Data Modelling & Structure

• Design and implement logical and physical data models for core business entities.
• Define data attributes, normalization rules, and relationships to ensure data consistency and integrity.
• Align models with business rules and system requirements to support downstream analytics and operational needs.

2. Data Mapping & Integration

• Create comprehensive data maps across enterprise systems.
• Define transformation logic, validation rules, and standardization protocols to enable seamless data integration.
• Ensure data compatibility and integrity across heterogeneous data sources and applications.

3. Data Pipelines & Transfer Mechanisms

• Design and implement robust ETL/ELT pipelines to automate data ingestion from both structured and unstructured sources.
• Optimize batch and streaming pipelines for efficient, low-latency data transfer.
• Support real-time data synchronization to meet operational and reporting requirements.