# Data Specialist - R01571442 at Brillio

Data Specialist - R01571442 at Brillio in Chennai, Tamil Nadu, India. Hybrid. Posted September 22, 2026.

- Company: Brillio
- Location: Chennai, Tamil Nadu, India
- Workplace: Hybrid
- Experience: 5+ years
- Posted: 2026-09-22
- Apply: https://jobs.lever.co/brillio-2/4eab5886-5daf-42f2-bdfb-e0fb8dcc8b8c/apply
- Source: https://jobmagic.ai/jobs/data-specialist-r01571442-brillio-xtdg5z

## Requirements

- Work with pricing analysts to identify custom definitions, calculations, transformations, dependencies, assumptions, edge cases, and ambiguities currently implemented in the Gold layer.
- Reverse-engineer analyst-written SQL, spreadsheet logic, and ad hoc calculations to define intended business behaviour.
- Translate legacy logic into clear technical requirements and migration plans.
- Re-implement approved pricing definitions as governed, reusable, documented dbt models in the Silver layer.
- Follow data modelling, naming, testing, version control, and code review standards.
- Build maintainable, scalable, auditable models independent of undocumented analyst knowledge.
- Apply dbt tests for uniqueness, not-null, accepted values, relationships, and business rules.
- Compare migrated Silver-layer results with existing Gold-layer outputs and resolve differences.
- Validate results across representative periods, segments, boundary conditions, and known exceptions.
- Confirm migrations only after parity review and pricing analyst approval.
- Partner with pricing analysts to clarify calculations, confirm intended behaviour, and align on expected results.
- Lead walkthroughs and reviews; document analyst approval before retiring legacy definitions.
- Communicate risks, open questions, dependencies, and decisions to technical and business stakeholders.
- Document business meaning, calculation rules, assumptions, exceptions, source inputs, ownership, lineage, tests, and downstream consumers in dbt and Confluence.
- Ensure documentation enables future engineers and analysts to maintain logic without relying on the original analyst.

## Description

**Data Specialist**

### Job requirements

**Key Responsibilities Logic Discovery and Requirements Analysis**

- Work with pricing analysts to identify custom definitions, calculations, transformations, dependencies, assumptions, edge cases, and ambiguities currently implemented in the Gold layer.

- Reverse-engineer analyst-written SQL, spreadsheet logic, and ad hoc calculations to define intended business behaviour.

- Translate legacy logic into clear technical requirements and migration plans.

**Migration to the Silver Layer**

- Re-implement approved pricing definitions as governed, reusable, documented dbt models in the Silver layer.

- Follow data modelling, naming, testing, version control, and code review standards.

- Build maintainable, scalable, auditable models independent of undocumented analyst knowledge.

- Apply dbt tests for uniqueness, not-null, accepted values, relationships, and business rules.

**Parity Validation and Quality Assurance**

- Compare migrated Silver-layer results with existing Gold-layer outputs and resolve differences.

- Validate results across representative periods, segments, boundary conditions, and known exceptions.

- Confirm migrations only after parity review and pricing analyst approval.

**Analyst Collaboration and Sign-Off**

- Partner with pricing analysts to clarify calculations, confirm intended behaviour, and align on expected results.

- Lead walkthroughs and reviews; document analyst approval before retiring legacy definitions.

- Communicate risks, open questions, dependencies, and decisions to technical and business stakeholders.

**Documentation and Lineage**

- Document business meaning, calculation rules, assumptions, exceptions, source inputs, ownership, lineage, tests, and downstream consumers in dbt and Confluence.

- Ensure documentation enables future engineers and analysts to maintain logic without relying on the original analyst.

**Gold-Layer Cleanup and Cutover**

- Decommission ad hoc Gold-layer logic after the Silver replacement is validated, approved, adopted, and downstream dependencies are updated.

- Verify retired logic is no longer used and operational documentation reflects the new source of truth.

**Required Qualifications**

- 5–8 years of data engineering experience on analytical data platforms.

- Strong SQL skills: joins, window functions, CTEs, aggregations, conditional logic, and optimisation.

- Hands-on dbt experience across models, tests, documentation, and lineage.

- Strong Snowflake experience, including modelling, performance tuning, and warehouse concepts.

- Experience refactoring, migrating, or modernising complex analytical logic.

- Ability to untangle ad hoc SQL and spreadsheet calculations and validate outputs.

- Strong understanding of data quality, reconciliation, testing, and release controls.

- Skilled at working with non-engineering stakeholders to clarify requirements and validate outcomes.

- Excellent communication and documentation habits.

**Core Skills and Tools**

- SQL; Python a plus

- Snowflake

- dbt, dbt Cloud

- Airflow

- Confluence, Jira, Slack

- Data modelling, quality validation, reconciliation, migration planning, stakeholder collaboration, and technical documentation.