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Data Engineer

Avencia Consulting
London, United Kingdom
2 weeks ago
Applications closed

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Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Mid
Education
Degree
Posted
30 Apr 2026 (2 weeks ago)
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About us

HDI is a Corporate & Specialty Insurer part of the Talanx Group. With over 120 years of experience, HDI operates across five continents, around 40 countries and employs over 5,000 people worldwide.

The role

The Data Engineer is responsible for designing, building, and maintaining robust, scalable data pipelines and cloud-based data infrastructure to support analytics, reporting, data modelling, underwriting insights, and regulatory needs across HDI UK&I.

This role ensures timely, trusted, well-structured data delivery into appropriate data marts & warehouses, and downstream data feeds which are used by Actuarial, Finance, Operations, and Underwriting.

The position forms a core part of HDI's data transformation agenda, enabling improved decision-making, automation, and analytics maturity.

Key accountabilities

Data Pipeline Engineering & Integration

  • Design, develop, and maintain end to end ingestion pipelines into appropriate data technologies such as Snowflake from internal systems (policy admin, claims, finance) and external data sources.
  • Build orchestrated ELT/ETL processes using modern tooling and best practice engineering patterns.
  • Implement incremental refresh, schema evolution management, and data validation tests.
  • Ensure data availability aligned to business SLAs (e.g., daily refresh for actuarial & finance repositories).

Data Modelling & Warehouse Development

  • Create well-structured dimensional and relational data models for analytical use cases.
  • Develop canonical, reusable datasets (curated marts) for Analytics, Actuarial, and Finance.
  • Own the technical modelling layer in Snowflake including schema design, performance optimisation, cost control, and warehouse governance.
  • Collaborate closely with Analytics Engineers using dbt, ensuring transformations are production-grade, tested, and fully documented.

Data Quality, Testing & Governance

  • Implement automated testing suites, data contracts, lineage, and monitoring frameworks.
  • Partner with Data Governance to embed quality rules, SLAs, and metadata standards into pipelines.
  • Resolve data quality issues proactively and own improvements to source-to-target data flows.

Cross-Functional Collaboration

  • Work with business areas as needed to supply structured data sets for relevant business processes.
  • Drive the building of automated, trusted data feeds for analytics requirements.
  • Partner with Data Analysts to accelerate dashboarding and advanced analytics.
  • Collaborate with Technology teams to ensure secure, reliable platform operation.

Performance, Optimisation & Cost Efficiency

  • Optimise Snowflake/SQL/Python query performance, warehouse sizing, storage costs, and compute efficiency.
  • Implement workload separation, time travel optimisation, clustering, and pruning strategies.

Documentation & Knowledge Sharing

  • Produce comprehensive documentation for pipelines, data models, data flows, and architecture components.
  • Provide technical guidance to junior team members and evangelise engineering best practices.

Skills & experience

Technical Skills

  • Expert SQL engineering capability
  • Advanced experience with schemas, warehouses, stages, tasks, streams, performance tuning.
  • Experience of modern transformation frameworks (Snowflake/DBT preferred - but not essential)
  • Python for scripting, automation, and orchestration.
  • Experience with CICD pipelines (GitHub Actions / Azure DevOps), code reviews, and versioning.
  • Strong understanding ofdata modelling, data warehousing patterns, and ELT best practice.
  • Familiarity withPowerBI or BI model structures to support downstream analytics.
  • Cloud platform experience (Azure preferred).

Business & Domain Skills

  • Prior experience ininsurance, especially commercial/specialty lines, claims, actuarial or finance data structures
  • Understanding of regulatory expectations around data quality, lineage, and auditability (desired but not essential)

Professional:

  • Degree in Computer Science, Engineering, Mathematics or similar (or equivalent professional experience).
  • dbt certification beneficial.
  • Snowflake certifications advantageous.

Other

As an equal opportunities employer, we are committed to creating an inclusive environment for all employees, recognising that a diverse and inclusive workplace is a creative and prosperous one.

If you require support with your application, please contact UK&

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