Data Engineer

• We design and implement data ingestion, transformation, and processing pipelines on Azure.
• We build and maintain scalable data pipelines for data cleaning, enrichment, and preparation.
• We apply appropriate data modelling techniques, including medallion architecture principles.
• We orchestrate and optimise Azure Databricks jobs and Azure Data Factory pipelines.
• We configure data platforms and compute resources to optimise cost, performance, and reliability.
• We implement CI/CD pipelines to deploy and manage data artefacts and workflows.
• We operationalise data workflows created by analysts and data scientists.
• We support customers in adopting Azure data, analytics, and machine learning services.
• We ensure secure storage, processing, and governance of data across environments.
• We apply networking and security best practices across all data solutions.
• We design solutions for large-scale data processing using batch and streaming approaches.
• We collaborate with analytics teams to support reporting and data visualisation use cases.
• We maintain clear and comprehensive technical documentation, including pipelines and runbooks.
• We support audits, risk assessments, and regulatory compliance requirements.
• We contribute to continuous improvement of data platforms, pipelines, and processes.

Technologies:

• AI
• Azure
• Big Data
• CI/CD
• Databricks
• Support
• Kafka
• Machine Learning
• Power BI
• Python
• SQL
• Scala
• Security
• Spark
• Cloud

• We require strong SQL skills.
• We require programming experience with Python and/or Scala.
• We require hands-on experience with Azure data platforms.
• We require experience building and maintaining data pipelines.
• We require a strong understanding of data modelling, including relational and analytical models.
• We require experience with Databricks and Data Factory orchestration.
• We require experience using CI/CD pipelines for data solutions.
• We require understanding of security, GDPR, PII, and data protection practices.
• We value a positive mindset and a strong willingness to learn new technologies.
• We need an analytical and methodical approach to problem-solving.
• We expect strong awareness of ethical data usage and compliance considerations.
• We require excellent communication skills with both technical and non-technical stakeholders.
• We prefer experience with Azure Databricks in production environments and familiarity with Azure Machine Learning and AI services.
• We prefer experience with data visualisation tools such as Power BI and big data frameworks such as Spark or Kafka.
• We prefer understanding of data governance, lineage, and metadata tools.

We are Claranet, and this role sits within our Data & AI Practice. We support financial services customers by delivering modern, secure, scalable Azure-based data platforms that enable ingestion, transformation, processing, analytics, and machine learning workloads. This is a hands-on role focused on reliable, auditable, and compliant data environments, working closely with customers, analysts, and platform teams. We offer a flexible benefits package that includes employer-matched pension contributions, private healthcare, discounted gym memberships, 24/7 wellbeing support, 25 days of annual leave rising to 27 with service plus bank holidays and your birthday off, and ongoing learning and development opportunities. We also have Team Claranet, our internal community that supports charitable causes, local initiatives, and company-wide fundraising events.