At a Glance
- Tasks: Design and build data infrastructure for a next-gen insurance analytics platform.
- Company: Join a leading insurance company focused on innovation and real-time decision-making.
- Benefits: Enjoy flexible working, private medical insurance, and a corporate bonus scheme.
- Other info: Collaborative environment with opportunities for mentorship and professional growth.
- Why this job: Make a real impact by optimising data solutions that drive customer offers.
- Qualifications: 3+ years in data engineering with strong skills in Python, SQL, and modern data frameworks.
The predicted salary is between 60000 - 80000 £ per year.
We are building a next‑generation insurance analytics platform that powers real‑time offer optimisation, market sensing, and model‑driven decision‑making across our personal lines products. This role is responsible for designing and building the data infrastructure in Microsoft Fabric that standardises, integrates, and delivers the data our actuarial, data science, and product teams depend on. You will own the pipelines that bring together internal claims, policy, and quoting data with external market signals into a unified, reliable data platform. Your work directly enables the models and systems that determine what we offer customers and how quickly we react to market shifts.
Key Responsibilities
- Design, Build & Manage Data Solutions — design, develop, and enhance scalable data pipelines and data processing systems; build reusable ingestion, transformation, and storage patterns to support product and analytical needs; integrate data from diverse sources including APIs, databases, event streams, and third‑party systems; implement data models and schemas that create unified, consistent views of business operations.
- Engineering Excellence — apply modern engineering practices, including version control, testing, CI/CD, and automated deployments; ensure data quality, integrity, and reliability through validation, monitoring, and observability tools; optimise data workflows for performance, cost efficiency, and operational resilience; document data flows, lineage, and technical components in support of transparency and maintainability.
- Product Collaboration & Delivery — collaborate closely with product managers, engineers, and analysts to understand data requirements; participate in iteration planning, ensuring shared understanding of backlog items and technical needs; engage in daily stand‑ups, retrospectives, and product ceremonies as an active member of the team.
- Governance, Standards & Continuous Improvement — contribute to data governance practices such as metadata management and data lineage; ensure compliance with data privacy, security, and regulatory requirements; evaluate new technologies, frameworks, and patterns to improve data infrastructure and engineering capabilities; share knowledge and mentor less experienced engineers, contributing to team growth and best practices.
Essential Skills
- Minimum of 3 years experience in a related field developing sophisticated big data pipelines in support of machine learning and advanced AI.
- Strong proficiency with data pipeline development in Python, Java, or Scala.
- Minimum of 3 years experience with modern data frameworks (Spark, Kafka, Flink, dbt, or equivalent).
- Minimum of 3 years experience with SQL and NoSQL databases and data modelling principles.
- Proven ability to optimise SQL, pipelines and storage for performance and cost.
- Experience building batch and/or streaming data solutions.
- Experience using Microsoft Fabric Notebooks to develop, debug, and operationalise data engineering workflows.
Desirable Skills
- A degree of any level in a quantitative field such as mathematics, physics or computer science with a classification of 2.1 or higher (or equivalent).
- Experience with cloud data services (Azure, AWS).
- Experience with observability and monitoring tools.
- Hands‑on experience with Microsoft Fabric components, including Lakehouse, Warehouse, Data Pipelines, Dataflows Gen2, and Semantic Models.
- Familiarity with CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps, etc.).
- Performance tuning for data pipelines, databases, and queries.
- Familiarity with generative and agentic AI tools to improve engineering productivity.
- Experience with containerisation and orchestration tools (Docker, Kubernetes).
Supervisory Responsibilities
This job does not have supervisory duties.
Legal Requirement
All applicants must demonstrate they have the legal right to work for employment at Allstate.
Benefits
- Corporate bonus scheme
- Pension scheme
- Annual performance‑related pay reviews
- Life assurance and income protection
- Flexible working options
- Hybrid working
- Private medical and dental insurance
- Access to an employee assistance programme
- Discounted gym membership
- Two paid volunteering days each year
- Cycle to work scheme
Data Analytics Engineer- Senior Consultant II employer: Allstate NI
At Allstate, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Senior Consultant II in Data Analytics Engineering, you will have the opportunity to work on cutting-edge projects within our next-generation insurance analytics platform, while enjoying benefits such as flexible working options, a corporate bonus scheme, and access to professional development resources. Our commitment to employee growth and well-being, combined with a supportive environment, makes Allstate a rewarding place to advance your career.
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We think you need these skills to ace Data Analytics Engineer- Senior Consultant II
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