Senior Data Engineering Specialist

Roles and Responsibilities
Technical Leadership: Cloud Architecture & Data Engineering
Cloud Solution Design: Architect scalable, secure, and cost-effective cloud solutions using Azure technologies, addressing multi-domain requirements. Key services include:
Azure Data Factory: Automated and orchestrated data pipelines.
Azure Synapse Analytics: Scalable data warehousing and analytics.
Azure Databricks: Data processing, machine learning, and real-time analytics.
Azure DevOps: CI/CD pipelines, infrastructure automation, and monitoring.
Data Pipeline Development: Build robust ETL/ELT pipelines to ingest, process, and manage structured, semi-structured, and unstructured data.

Key Qualifications and Experience
Technical Expertise
Cloud Technologies:
Advanced knowledge of Azure Data Factory, Synapse Analytics, Databricks, Azure SQL, and Azure DevOps.
Proficiency in cloud cost management, security, and compliance frameworks (e.g., GDPR, HIPAA).

Programming & Tools:
Expert in Python, SQL, Spark, and distributed computing frameworks.
Familiarity with machine learning tools and libraries (e.g., TensorFlow, Scikit-learn).

Data Strategy:
Strong understanding of data modelling, governance, quality assurance, and metadata management.

Professional Experience
Years of Experience:
Minimum 12+ years in data engineering or cloud architecture, with 6+ years of Azure-specific experience.

Project Delivery:
Demonstrated success delivering 5+ large-scale, multi-industry projects, each involving significant business impact and cross-functional collaboration.