Data Architecture & Strategy
- Architect end‑to‑end data solutions across Azure ecosystems (Databricks, Synapse, Data Factory).
- Define standards for data modelling, governance, integration, and lifecycle management.
- Drive the adoption of best practices such as Delta Lake, medallion architecture, and Lakehouse patterns.
Advanced Pipeline Development
- Design, develop, and optimize complex ETL/ELT pipelines using Azure Databricks (Python, PySpark, SQL).
- Lead orchestration across Azure Data Factory and implement CI/CD for data workflows.
- Ensure solutions meet enterprise performance, scalability, and availability requirements.
Data Warehousing & Lakehouse Optimization
- Lead the design and enhancement of data warehouses and lakehouse systems with Azure Synapse Analytics.
- Implement partitioning, clustering, and performance‑tuning strategies to support large‑scale financial datasets.
Data Integration & Quality
- Oversee integration of structured, semi‑structured, and unstructured data from multiple internal and external sources.
- Implement robust data quality frameworks, monitoring, and observability solutions.
Security, Compliance & Governance
- Ensure all data solutions adhere to financial industry regulations (e.g., GDPR, PCI‑DSS).
- Drive adoption of access controls, encryption standards, and secure data handling practices.
Leadership & Mentorship
- Provide technical guidance, code review, and mentorship to junior and mid‑level engineers.
- Collaborate with cross‑functional teams—including data science, analytics, product, and architecture groups—to translate business requirements into scalable data solutions.
Monitoring, Troubleshooting & Optimization
- Own operational reliability of data platforms.
- Diagnose performance issues and drive continuous improvement across data workloads.
