Skills Required Primary Skills P&C; Insurance Domain; Medallion architecture; Advanced SQL; Data VaultXMLJson; STTM Job Description Key Responsibilities

Elicit and document data requirements from QBE SMEs, product owners, and reporting/actuarial consumers; run structured workshops and follow-ups across time zones.

Profile and analyse source system data (SQL against SQL Server/Oracle/Databricks) to assess quality, completeness, grain, and edge cases before build starts.

Author precise source-to-target mapping (STM) specifications: field-level mappings, transformation and derivation logic, filter/join rules, SCD behaviour, reject/exception handling, and reference-data lookups.

Define data quality rules and acceptance criteria per dataset; agree reconciliation and control totals with business and testing teams.

Maintain the business glossary and metadata for owned subject areas; align terminology with the Data Modeler's entities and the governance team's definitions.

Support engineering during build - clarify specs, adjudicate discrepancies, review outputs against mappings; support SIT/UAT with test-scenario design and defect triage.

Perform impact analysis for change requests and source-system changes; keep STMs versioned and current.

Produce clear analysis artefacts and walkthroughs for onshore stakeholders; convert ambiguous asks into decisions with documented assumptions.

Must-Have Skills & Experience

9 12 years total with strong recent experience as a data/business analyst on data warehouse or lakehouse programmes.





Advanced SQL for profiling and validation on large datasets (window functions, aggregation reconciliation); comfort querying Databricks (Spark SQL) directly.

Proven authorship of source-to-target mappings and transformation specifications consumed by engineering teams.

Insurance domain depth - P&C; preferred: policy lifecycle, claims lifecycle, premium/exposure, bordereaux/reinsurance concepts, and typical KPI/reporting needs.

Data quality analysis: rule definition, exception analysis, reconciliation approaches.

Agile delivery experience with Jira/Confluence artefact discipline.

Excellent stakeholder management and written documentation - specs a new engineer can build from without a meeting.

Good-to-Have

Exposure to Databricks/PySpark concepts (enough to review engineering logic), Power BI semantic models, or actuarial data marts.

Guidewire/Duck Creek or London-market data structures; ACORD standards.

Python/pandas for ad-hoc analysis; Alteryx; data catalog tools (Purview/Collibra).

Insurance certifications (III/CII/AINS) a plus.

Qualifications

Bachelor's degree; business, finance, statistics, or computer science preferred.

Qualified & Communication Skills

Sharp requirements-to-decision facilitation; keeps ambiguity from reaching the sprint.

Confident, concise English for daily onshore interaction and SME workshops.

Detail obsession with an audit trail - every mapping decision traceable to a source and an owner.

📌 Business Data Analyst (BDA) – Insurance Data (India)
🏢 Sparix Global
📍 India