Data Engineer

As a Data Engineer at LevelShift, you will:

• Design, develop, and maintain scalable data models and data warehouses to support enterprise reporting and analytics requirements.
• Build reports using Power BI, Tableau, to deliver meaningful business insights.
• Develop and manage ETL/ELT pipelines to enable efficient data integration, transformation, and processing across multiple data sources.
• Implement data quality, governance, security controls, and access management practices to ensure trusted and compliant data environments.
• Collaborate with business stakeholders and technical teams to gather requirements, optimize data workflows, and support cloud-based data modernization initiatives.

How this role uses AI

• Should be comfortable using AI tools to enhance analytics workflows, automate repetitive tasks, generate insights, and improve productivity while ensuring data governance and security.
• Utilize AI-assisted data preparation, dashboard generation, anomaly detection, predictive analytics, documentation, and code generation to accelerate solution delivery.
• Leverage AI-powered tools such as Microsoft Copilot, Power BI Copilot, Azure AI services, GitHub Copilot, and cloud-native analytics platforms to build intelligent and data-driven solutions.

Your Skillset

• Bachelors degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
• 3+ years of experience in data engineering, business intelligence, analytics, or related data platform roles.
• Strong hands-on experience in data modeling, dimensional modeling, and data warehousing concepts.
• Expertise in reporting tools such as Power BI, Tableau., Experience/Certification in MS Fabric
• Experience implementing data-level security, role-based access controls, and data governance frameworks.
• Hands-on knowledge of ETL/ELT frameworks, data integration processes, and pipeline orchestration.
• Strong understanding of Data Quality Management principles and best practices.
• Experience working with cloud-based data platforms like Azure
• Strong SQL skills with experience querying and optimizing large datasets.
• Excellent analytical, problem-solving, and communication skills with the ability to translate business requirements into scalable data solutions.
• Passion for continuous learning and staying current with emerging data technologies, cloud services, and AI-driven analytics.
• Knowledge of Python for data analysis, automation, or analytical model development is an added advantage.