Data Engineer

2 months ago

United Kingdom NearTech Search Full time

My client is seeking a skilled Senior Data Engineer to join their team as they develop a modern, scalable, and automated data architecture. The successful candidate will be at the forefront of automating the collection and standardisation of diverse datasets, enabling data-driven decision-making across the organisation. This is an exciting opportunity for someone with a strong background in Azure services and a keen interest in leveraging Large Language Models (LLMs) to streamline manual data processes.

Key Responsibilities:

  • Data Engineering & Architecture: Design, build, and maintain scalable data pipelines using Azure Data Factory, Databricks, and Synapse Analytics.
  • Data Collection & Standardisation: Develop tools to collect and standardise data from various sources, ensuring consistent and accurate representation of values.
  • Automation & Optimisation: Utilise LLMs to classify and align data sets, automating manual processes and improving operational efficiency.
  • Model Deployment: Support the training and deployment of machine learning models, ensuring they’re integrated into data pipelines and accessible through APIs.
  • Cross-functional Collaboration: Partner with product and engineering teams to understand their data needs and provide solutions that enhance their capabilities.
  • Innovation & Proof of Concept (PoC): Design and implement PoCs to demonstrate the value of new data solutions and technologies to internal stakeholders.

Required Skills & Experience:

  • Strong experience with Azure-managed services (Azure Data Lake, Data Factory, Databricks, Event Hubs, Synapse Analytics).
  • Proficient in Python and CI/CD pipeline implementation.
  • Hands-on experience with LLMs or classification models, particularly in using supervised learning methods.
  • Demonstrated ability to build and deploy APIs or interfaces that integrate with other systems.
  • Proven track record of creating scalable data solutions that drive business outcomes.
  • Experience in working with large, bespoke data sets and resolving issues related to data consistency.

Preferred Qualifications:

  • Understanding of how to incorporate ML models into data architectures and enhance pipelines using advanced analytics.
  • Ability to build and refine automated systems to eliminate manual data processing tasks.

Benefits:

  • Competitive salary and benefits package.
  • Flexible working hours with a hybrid setup.
  • Opportunity to work on cutting-edge data solutions that drive innovation.

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