Data Engineer(Azure Data Platform)

Job Summary The Data Engineer will be responsible for designing, developing, and maintaining data pipelines and warehouse solutions within the Azure ecosystem. This role plays a critical part in ensuring the reliability, security, and scalability of data infrastructure, enabling the organization to leverage data for analytics, reporting, and business decision‑making. The ideal candidate combines strong technical expertise with a keen understanding of data governance, quality, and compliance. Key Responsibilities Design, build, and maintain ETL/ELT pipelines using Azure Data Factory, Python, and SQL to extract and transform data from multiple internal and cloud systems. Develop and manage data staging environments to prepare and validate data before integration into production systems. Build and optimize data warehouses and datamarts within Azure SQL Database and Azure Synapse Analytics to support reporting, dashboards, and analytics. Implement data redundancy, backup, and recovery strategies to ensure business continuity and data integrity. Collaborate with the BI Manager, BI developers, and business teams to define requirements and deliver reliable, high‑performance datasets for analysis. Lead the implementation of data governance rules and enforce access controls, data lineage tracking, and quality assurance processes across the Azure environment. Ensure compliance with data privacy and protection standards through proper security, encryption, and audit measures. Continuously monitor and optimize data workflows for performance, scalability, and cost efficiency. Partner with business and system owners to enhance data integrations between BMS, Getz Clinical, and other platforms. Qualifications Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field. 4+ years of experience in data engineering, data warehousing, or Azure data solutions. Strong proficiency in SQL, Python, and ETL/ELT tools such as Azure Data Factory (ADF) and/or Pentaho Data Integration (PDI/Kettle) for pipeline design and orchestration. Hands‑on experience with Azure SQL Database, Azure Synapse Analytics, and Azure Data Lake Storage. Proven understanding of data staging, redundancy management, datamart design, and data warehousing best practices. Familiarity with Power BI, Tableau, or equivalent visualization tools. Experience implementing data governance, metadata management, and data privacy frameworks. Excellent communication and collaboration skills, with the ability to translate technical concepts into business value. Preferred Skills Strong understanding of data engineering principles, including ETL/ELT processes and data pipeline orchestration. Proficiency in SQL and Python for data extraction, transformation, and automation. In-depth knowledge of data warehousing, modeling, and optimization for analytics and reporting. Familiarity with data governance, lineage, and quality assurance frameworks. Expertise in data integration and interoperability across multiple systems and cloud environments. Ability to ensure data security, privacy, and compliance with organizational and regulatory standards. Skilled in performance tuning, scalability, and cost optimization of data workflows. Ability to design and manage redundancy, backup, and recovery strategies for business continuity. Strong analytical and problem‑solving skills for troubleshooting data and system issues. Excellent collaboration and communication abilities to align technical solutions with business needs. Experience with Azure Purview, Microsoft Fabric, or similar data cataloging tools. Knowledge of CI/CD pipelines, Azure DevOps, and infrastructure‑as‑code frameworks (e.g., Terraform, Bicep). Background in healthcare, CRM, or retail data systems. Exposure to real‑time data processing and streaming data integration. #J-18808-Ljbffr