As a Data Architect, you will own our SQL data estate, design scalable pipelines, and lead data enrichment across our Azure-first platform. You’ll set the standards for modelling, quality, security, and cost while writing production-grade Python and SQL daily.
- Design and evolve schemas for OLTP/OLAP (Azure SQL, Synapse, Delta Lake), with partitioning, indexing, and RLS for multi-tenant isolation.
- Establish data contracts and versioning, govern schema evolution, and implement CDC +SCD patterns.
- Performance engineering: query tuning, resource classes, caching strategies, and cost guardrails.
- Architect ELT/ETL across batch & streaming using Azure Data
- Factory/Synapse/Databricks, Event Hubs/Service Bus, Functions, and Container Apps/AKS.
- Build reliable, observable pipelines (idempotent, retryable, lineage-aware) with SLAs/SLOs and runbooks.
- Implement CI/CD for data (dbt/SQL projects, PySpark jobs, tests) using GitHub Actions and IaC (Terraform/Bicep).
- Define and operate enrichment layers: UPC/GS1, OCR/EXIF metadata, taxonomies, embeddings, and third-party data joins.
- Curate gold/semantic models for analytics & product APIs; manage feature/metric definitions and documentation.
- Partner with DS/ML to operationalize feature stores, model outputs, drift signals, and evaluation tables.
- Own reference architecture across ADLS Gen2, Synapse/Databricks, Azure SQL/SQL Server, Cosmos DB (incl. vector), Azure AI Search, Key Vault, Purview.
- Security & compliance by default: encryption, secret management, RBAC/ABAC, data retention and GDPR/SOC 2 controls.
- Observability: OpenTelemetry + Azure Monitor/App Insights, data quality tests, freshness SLAs, and lineage in Purview.
Requirements
- Extremely strong Python & SQL (you can diagnose complex query plans, write PySpark and pandas with equal ease).
- 7+ years in data engineering/architecture with production ownership of SQL databases and pipelines.
- Deep Azure experience: ADLS Gen2, Data Factory/Synapse/Databricks, Azure SQL/SQL Server, Functions, Event Hubs/Service Bus, Key Vault.
- Proven design skills in data modeling (star/snowflake, Data Vault/Lakehouse), CDC/SCD, and semantics (dbt or equivalent).
- Track record implementing data quality frameworks, lineage, and cost/performance guardrails at scale.
- Strong understanding of multi-tenant SaaS, security, and privacy (GDPR basics).
- Cosmos DB (incl. vector) and Azure AI Search; embedding pipelines for images/text.
- Feature stores, MLflow/registries, real-time inference plumbing.
- SQL Server internals, PolyBase/Serverless SQL; Postgres familiarity.
- Purview rollouts, governance programs, and data product operating models.
