Brillio
Brillio
Brillio is a technology consulting company helping organizations navigate digital transformation across healthcare, insurance, logistics, financial services, telecom and media, life sciences, and retail. Its work spans customer experience, data and AI, generative AI, product and platform engineering, and infrastructure, cloud, and security. Brillio combines engineering expertise with industry knowledge to develop digital products and modernize technology environments, helping businesses respond to changing market and technology demands.

Hybrid Data Engineer – dbt and Snowflake at Brillio

Join Brillio as a Data Engineer focused on reverse-engineering pricing logic and rebuilding it as governed Silver-layer dbt models. Validate parity, document lineage, and retire legacy Gold-layer definitions with analyst approval.

Description

  • Collaborate with pricing analysts to uncover Gold-layer definitions, calculations, transformations, dependencies, assumptions, edge cases, and ambiguities
  • Reverse-engineer analyst SQL, spreadsheet formulas, and ad hoc calculations to establish intended business behaviour
  • Convert legacy logic into defined technical requirements and practical migration plans
  • Build approved pricing definitions as governed, reusable, documented dbt models in the Silver layer
  • Apply established standards for data modelling, naming, testing, version control, and code review
  • Create scalable, maintainable, auditable models that do not depend on undocumented analyst knowledge
  • Implement dbt tests covering uniqueness, nullability, accepted values, relationships, and business rules
  • Reconcile Silver-layer outputs with existing Gold-layer results and investigate discrepancies
  • Test migrated results across representative time periods, segments, boundary conditions, and known exceptions
  • Complete migrations following parity review and pricing analyst approval
  • Work with pricing analysts to clarify calculations, confirm intended behaviour, and agree on expected results
  • Run walkthroughs and reviews while recording analyst approval before legacy definitions are retired
  • Keep technical and business stakeholders informed about risks, unresolved questions, dependencies, and decisions
  • Record business context, calculation rules, assumptions, exceptions, inputs, ownership, lineage, tests, and downstream consumers in dbt and Confluence
  • Retire ad hoc Gold-layer logic once the Silver replacement is validated, approved, adopted, and its downstream dependencies are updated
  • Confirm retired logic is no longer in use and update operational documentation to reflect the new source of truth

Requirements

  • Five to eight years of experience in data engineering for analytical data platforms
  • Advanced SQL proficiency, including joins, window functions, CTEs, aggregations, conditional logic, and optimisation
  • Practical dbt experience covering models, tests, documentation, and lineage
  • Strong Snowflake knowledge, including data modelling, performance tuning, and warehouse concepts
  • Background in refactoring, migrating, or modernising complex analytical logic
  • Ability to interpret ad hoc SQL and spreadsheet calculations and verify their outputs
  • Strong grasp of data quality, reconciliation, testing, and release controls
  • Ability to work with non-engineering stakeholders to clarify requirements and validate results
  • Clear communication and disciplined documentation practices
  • Python experience is a plus
  • Experience with Airflow, Confluence, Jira, and Slack
  • Experience spanning data modelling, quality validation, reconciliation, migration planning, stakeholder collaboration, and technical documentation

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