Data and Analytics Engineer, Enablement

Zensar Technologies Limited is seeking a highly skilled Data and Analytics Engineer to enable data engineers and analysts through best-practice data engineering in Microsoft Fabric and Databricks, and to create high-quality Power BI visualisations. The role collaborates with stakeholders to translate business needs into robust data products, semantic models, and self-service analytics, while driving modernisation of legacy BI assets and exploring AI-driven insights.

• 8+ years of experience in data engineering and analytics, preferably in enterprise environments.
• Hands-on expertise with Microsoft Fabric, Databricks, Delta Lake, and PySpark.
• Strong SQL skills and experience implementing CDC and incremental load patterns.
• Proficiency in Power BI development, DAX, and designing star-schema data models.
• Experience with CI/CD tools (e.g., Azure DevOps, Git) and Python automation scripting.
• Knowledge of data governance, security best practices, and data quality frameworks.
• Ability to translate business requirements into technical specifications and KPIs.
• Excellent communication and stakeholder management skills.
• Familiarity with AI/ML integration for conversational analytics is a plus.
• Bachelor s degree in Computer Science, Engineering, Data Science, or related field.

• Build and maintain bronze, silver, and gold lakehouse layers in Microsoft Fabric and Databricks using notebooks and PySpark.
• Implement incremental loading and change-data-capture pipelines from on-prem SQL sources to Fabric/Databricks, optimizing Delta tables for performance and cost.
• Translate business requirements into analytical specifications, define KPIs, and validate data product outputs during SQL-to-Lakehouse modernization.
• Design and govern Fabric semantic models and star schemas to support performant Power BI self-service reporting.
• Develop, optimize, and maintain interactive Power BI dashboards, including complex DAX calculations, row-level security, and usage monitoring.
• Create reusable Python scripts, CI/CD pipelines, and automation for data processing, report generation, and integration with external APIs.
• Define and deliver self-service analytics playbooks, training materials, and governed templates to empower business users.
• Establish playbooks for conversational and AI-driven analytics, ensuring semantic models support natural language queries and AI-generated insights.
• Support migration of legacy SSRS, SSAS, and SQL-based reports to modern Power BI and lakehouse solutions, validating parity and decommissioning artifacts.
• Continuously improve data processes, promote standards, and contribute to COE knowledge-sharing initiatives focused on data quality, governance, and security.