Roles and Responsibilities

• Design, develop, and maintain scalable and efficient data pipelines in Azure Databricks.
• Collaborate with data architects and analysts to implement robust data models and support business KPIs.
• Integrate data from various on-premise ERP and ETL systems (e.g., Informatica PowerCenter, IICS, Cognos, Netezza or equivalent).
• Participate in architecture and design reviews to support continuous improvement of the data platform.
• Ensure data quality, reliability, and governance across pipelines and datasets.
• Work within the Azure ecosystem, leveraging services such as Azure Data Lake, Azure Data Factory, Azure Synapse, and others.
• Collaborate with analytics and data science teams using platforms such as Power BI and Azure ML.
• Provide technical leadership and mentoring to junior team members.
• Troubleshoot complex data issues and implement corrective solutions.

Required Qualifications

• 5–10 years of experience in Data Engineering, Data Warehousing, or Data Integration projects.
• Strong engineering foundation with a focus on building and scaling data platforms.
• Hands-on experience with Azure Databricks and Spark-based solutions.
• Strong understanding of data modeling techniques and their impact on reporting and KPIs.
• Experience integrating with on-premise systems and familiarity with enterprise ETL tools (e.g., Informatica, Cognos, Netezza).
• Proven experience working in the Azure cloud ecosystem.
• Familiarity with analytical platforms such as Power BI and/or Azure Machine Learning.
• Strong problem-solving and communication skills.

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