Data Analytics Engineer
Role details
Job location
Tech stack
Job description
- Design and Deliver: Translate core business processes into clear, trusted data models and datasets for reporting and analytics.
- Data Engineering: Build and maintain scalable data pipelines across on-premises and Azure platforms, using tools such as Databricks, Fabric, SSIS, Azure Data Factory, APIs, and event-driven patterns.
- Analytics Development: Create and optimise SQL transformations, Power BI datasets/reports (including DAX), and Databricks or Microsoft Fabric notebooks using SQL and Python.
- Quality and Performance: Apply data quality, validation, and observability practices; troubleshoot and optimise pipelines, jobs, and reports for reliability and cost efficiency.
- Integration: Ensure interoperability between legacy systems and modern cloud solutions.
- Collaboration: Work closely with stakeholders to gather requirements and deliver solutions aligned with business outcomes.
- Operational Support: Participate in monitoring, incident response, and service desk support for data platforms and analytics products.
- Continuous Improvement: Identify opportunities for automation and enhanced data availability; contribute to CI/CD pipelines and follow best practices using Git and Azure DevOps.
- Team Contribution: Share knowledge, maintain documentation, and mentor associate engineers through peer reviews and guidance.
Requirements
Do you have experience in Scalability?, * Strong SQL (query optimisation, data modelling) and dimensional modelling expertise.
- Experience with Microsoft data platforms and tools (SSIS, Azure Data Factory, Databricks/Microsoft Fabric).
- Working knowledge of Python/PySpark for data transformation and automation.
- Integration experience with APIs and Power BI (datasets, semantic models, DAX).
- Familiarity with Azure Data Lake/Fabric storage, Git, and CI/CD pipelines.
- Understanding of scalability, observability, security, and cost control.
Desirable
- Near-real-time/event-driven ingestion; forecasting and optimisation use cases.
- Exposure to machine learning concepts and Python libraries (pandas, numpy, scikit-learn).
- Awareness of AI techniques (NLP, anomaly detection) and their business value.
- Certifications in Fabric or Databricks.
Behaviours
- Takes ownership and accountability for outcomes.
- Communicates clearly and collaborates effectively across teams.
- Proactive in learning and receptive to feedback.
Benefits & conditions
At Jersey Post, we believe in going above and beyond to ensure our employees feel valued, supported, and excited about their work.
Some benefits we offer is a great DC Pension Scheme, designed to secure your financial future. 31 days of Annual Leave, allowing you to take those well-deserved vacations, spend quality time with your loved ones, and recharge your batteries. Jersey Post offer flexible and hybrid working. An incredible annual 20% discretionary bonus.
Your health matters to us, which is why we provide a comprehensive Health and Dental cash plan. This means you'll have access to support, ensuring you can take care of yourself both physically and mentally.
As a valued member of our team, you'll gain access to an range of partner benefits and discounts, both in Jersey and online. Whether it's exclusive deals on shopping, dining, entertainment, or travel, we've got you covered.
About Jersey Post Group
At The Jersey Post Group we are fully committed to attracting and retaining the right people. We embrace diversity and have a range of interesting roles across business process, data management, ICT and operational disciplines.
Working across The Jersey Post Group offers opportunities for personal and professional development in an organisation that is both flexible and modern.
