Data Engineer

• Design, develop, and maintain enterprise-grade data pipelines using Microsoft Fabric and Azure Synapse Analytics.
• Build, optimize, and support ETL/ELT processes for ingesting and transforming data from multiple source systems.
• Develop and maintain Azure Synapse Pipelines, Fabric Data Factory Pipelines, and orchestration workflows.
• Create, maintain, and optimize Notebooks using Python, PySpark, and SQL for data transformation and validation activities.
• Design and implement data models that support reporting, self-service analytics, and dashboard requirements.
• Develop complex SQL queries, views, stored procedures, and transformation logic.
• Build reusable data engineering solutions for automation, monitoring, and operational reporting.
• Monitor pipeline performance, troubleshoot failures, and implement proactive alerting and monitoring mechanisms.
• Perform data quality assessments, data reconciliation, and root-cause analysis for production issues.
• Work with Lakehouse, Data Warehouse, and cloud-based analytical platforms to support enterprise reporting initiatives.
• Collaborate with Business Intelligence and Solution Design teams to deliver reporting-ready curated datasets.
• Participate in solution architecture discussions and recommend scalable and efficient data engineering approaches.
• Maintain technical documentation, data lineage, process flows, and operational runbooks.
• Support deployment activities, release management, and CI/CD best practices.
• Mentor junior team members and contribute to continuous improvement initiatives.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related discipline.
• 2–4 years of experience in Data Engineering, Analytics Engineering, or Business Intelligence.
• Strong experience with SQL and relational database concepts.
• Hands-on experience with Python for data transformation and automation.
• Experience building ETL/ELT solutions using Azure Synapse Analytics, Microsoft Fabric, Azure Data Factory, or similar platforms.
• Experience developing and supporting Data Pipelines and Notebooks.
• Knowledge of Data Warehousing and Dimensional Data Modeling concepts.
• Experience working with cloud-based analytics platforms and modern data architectures.
• Strong analytical, troubleshooting, and problem-solving skills.
  • Good verbal and written communication skills.