At a Glance
- Tasks: Design and optimise data architecture for SQL/PostgreSQL platforms in the insurance domain.
- Company: Leading insurance firm focused on innovative data solutions.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on modernisation and data governance.
- Why this job: Shape the future of data in insurance and drive impactful change.
- Qualifications: Experience in SQL/PostgreSQL and a strong background in insurance processes.
The predicted salary is between 72000 - 88000 £ per year.
Responsibilities
- Define and own end-to-end data architecture for SQL/Postgre SQL-based platforms across transactional, analytical, and reporting workloads.
- Design logical and physical data models, database schemas, data flows, integration patterns, and data migration strategies.
- Partner with business stakeholders, product owners, data engineers, application teams, and enterprise architects to translate insurance business requirements into scalable data solutions.
- Lead database modernisation, optimisation, and migration initiatives involving SQL Server, Postgre SQL, or cloud-native Postgre SQL platforms.
- Establish data architecture standards covering data quality, metadata, lineage, retention, security, privacy, and regulatory compliance.
- Review and optimise database performance, indexing strategies, partitioning, query design, stored procedures, and data access patterns.
- Support data governance and master/reference data management initiatives across insurance data domains.
- Provide architectural guidance, design reviews, and technical leadership to engineering and delivery teams.
We are looking for an experienced SQL/Postgre SQL Data Architect with a strong insurance domain background to design, modernise, and govern enterprise data platforms.
The candidate must bring hands-on expertise in relational database architecture, data modelling, performance optimisation, data migration, and data governance, with proven experience supporting insurance business functions such as policy administration, claims, underwriting, billing, customer, broker, risk, or reinsurance data., Strong hands-on experience as a Data Architect, Database Architect, or Senior Data Modeller working on enterprise-scale data platforms.
Requirements
- Mandatory insurance domain experience, with practical understanding of insurance processes such as policy lifecycle, claims, underwriting, billing, customer/account data, broker/intermediary data, risk, exposure, or reinsurance.
- Advanced SQL expertise, including complex query design, stored procedures, functions, views, indexing, partitioning, transaction handling, and performance tuning.
- Strong Postgre SQL experience, including schema design, database optimisation, security, backup/recovery concepts, replication, and high-availability design considerations.
- Experience designing logical, conceptual, and physical data models for operational and analytical use cases.
- Strong understanding of data warehousing, data marts, ETL/ELT patterns, data integration, and data migration approaches.
- Experience with data quality, data governance, metadata management, lineage, access control, and data security practices.
- Ability to assess existing data landscapes and recommend modernisation, rationalisation, and migration roadmaps.
- Experience working with large, complex, and highly regulated data environments.
- Strong stakeholder management and communication skills, with the ability to explain data architecture decisions to both technical and business audiences.
- Good to Have
- Experience with insurance data standards such as ACORD or equivalent canonical insurance data models.
- Experience with cloud database platforms such as AWS Aurora Postgre SQL, Azure Database for Postgre SQL, Amazon RDS, or Google Cloud SQL.
- Exposure to SQL Server to Postgre SQL migration, database refactoring, or Legacy data platform modernisation.
- Knowledge of data lake, lakehouse, or modern analytics platforms such as Snowflake, Databricks, Redshift, Synapse, or Fabric.
- Experience with ETL/ELT and data integration tools such as Informatica, Talend, dbt, Airflow, SSIS, Glue, or similar platforms.
- Understanding of regulatory and compliance expectations relevant to insurance data, including data privacy, retention, auditability, and operational resilience.
- Experience with master data management, reference data management, and golden-source data design.
- Familiarity with Dev Ops/Data Ops practices, CI/CD for database changes, version control, automated testing, and deployment pipelines.
- Ability to lead architecture workshops and produce high-quality design documentation, architecture decision records, and data standards.
- #J-18808-Ljbffr
Data Architect - Insurance Domain employer: Dns Info Ltd
As a Forward Deployed AI Engineer, you will thrive in a dynamic and innovative environment that prioritises collaboration and growth. Our company fosters a culture of continuous learning, offering ample opportunities for professional development while working on cutting-edge AI solutions that directly impact Corporate, Compliance, Legal, and Risk Management functions. Located in a fast-paced, regulated setting, we empower our employees to take ownership of their projects, ensuring meaningful contributions and rewarding experiences.
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We think this is how you could land Data Architect - Insurance Domain
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We think you need these skills to ace Data Architect - Insurance Domain
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
