We are looking for a highly skilled Senior Data Engineer / Data Architect with deep hands‑on expertise in Azure, Databricks, PySpark, Python, SQL, and modern data warehousing. This role is ideal for someone who has built large‑scale data platforms, designed enterprise‑grade architectures, and delivered high‑quality data products in cloud environments.
Core Technical Expertise
Azure Cloud Platform
- ADLS Gen2, ADF, Synapse, Azure SQL, Key Vault, App Services
- Cloud‑native architecture design, scalability, and cost optimization
- Security & governance: RBAC, Managed Identity, Private Endpoints
Databricks Engineering
- End‑to‑end development on Azure Databricks
- Lakehouse architecture implementation
- Delta Live Tables (DLT), Unity Catalog
- Performance tuning, cluster optimization
- CI/CD for Databricks workloads
Big Data & Processing Frameworks
- Apache Spark with advanced PySpark transformations
- Structured Streaming & batch data pipelines
- Delta Lake architecture & optimization
Programming & Querying
- Python for automation, data engineering, and orchestration
- PySpark for distributed data processing
- SQL for complex query optimization and analytics engineering
Data Architecture & Engineering
- Enterprise Data Warehouse (EDW) architecture
- Dimensional modeling (Star/Snowflake)
- Data Vault 2.0 modeling
- Metadata‑driven ingestion frameworks
- Change Data Capture (CDC) implementation
- Medallion architecture (Bronze/Silver/Gold)
- Data lineage, governance, cataloging
- Master Data Management (MDM)
Data Products & Analytics Enablement
- Design and delivery of scalable data products
- Business‑aligned semantic layer design
- KPI frameworks & enterprise reporting enablement
- Integration of ERP, SaaS, and operational systems
- Hybrid Lakehouse + EDW architectures
DevOps & Engineering Practices
- CI/CD pipelines (Azure DevOps, GitHub Actions, Bitbucket)
- Infrastructure as Code (Terraform, ARM templates)
- Automated testing (unit, integration, data quality)
- Monitoring, logging, and observability