Are you a passionate and enthusiastic data professional looking to build your career in data engineering, business intelligence, and analytics?
Join LevelShift as a Senior Software Engineer, where you'll design scalable data solutions, build modern analytics platforms, and transform data into actionable business insights. You'll collaborate with business stakeholders, data engineers, and analytics teams to deliver secure, high-quality, and cloud-enabled data solutions that drive informed decision-making across the enterprise.
What You'll Do
As a Senior Software 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 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.
