Data Engineer

Responsibilities:

• Gather business requirements, assess data gaps, and design scalable data architectures.
• Develop and implement data pipelines for data lakes and warehouses to support analytics.
• Build and manage ETL/ELT workflows ensuring data accuracy and cost efficiency.
• Perform data profiling, cleansing, and transformation for reporting.
• Monitor and optimize data warehouse performance, resolving bottlenecks.
• Ensure data security, compliance, and governance.
• Collaborate with Data Analysts to provide clean, structured data for reporting.
• Maintain and troubleshoot data pipelines, proactively addressing issues.
• Stay updated on industry trends and best practices in data engineering and analytics.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• 4+ years of experience with ETL/ELT pipelines, streaming data, and orchestration frameworks.
• Expertise in big data platforms, hybrid architectures, and cloud-native tools.
• Proficiency in SQL, Python, Java, with strong experience in Azure Databricks and SSIS automation. Familiarity with Azure Data Factory and Azure Synapse is a plus.
• Experience with large datasets, complex data models, and data modeling.
• Strong problem-solving, troubleshooting, and communication skills.
• Ability to work independently and manage projects effectively.
• Experience with Power BI or other visualization tools is a plus.
• Knowledge of auditing, logging, and ETL operations monitoring.