Engineer / Sr. Engg - DATA & Digital Solutions (M&M IC)

Key Responsibilities Design, develop, and maintain enterprise databases using SQL Server and PostgreSQL. Manage database performance, optimization, backup, recovery, and troubleshooting activities. Develop and maintain reports, dashboards, and MIS solutions using SQL Server Reporting Services (SSRS), Power BI, and Tableau. Develop and manage ETL/data integration workflows using SQL Server Integration Services (SSIS). Support integration of data from multiple business applications and digital platforms. Design and support scalable database architectures for enterprise digital tools and applications. Work with cloud-based Data platforms, Data lakes, and Databricks environments for modern data management and analytics. Analyse project and business data to identify trends, risks, opportunities, and efficiency improvement areas. Explore and support AI/ML-based analytics initiatives for predictive insights and smarter decision-making. Collaborate with cross-functional teams including IT, Engineering, Projects, Business, and Digital Transformation teams. Ensure data quality, data governance, security, and compliance with organizational standards. Provide technical support, troubleshooting, and enhancement support for reporting and analytics systems. Prepare technical documentation, SOPs, data dictionaries, and user guidelines. Coordinate with vendors and internal stakeholders for system improvements, integrations, and issue resolution. Soft Skills & Competencies Excellent communication and interpersonal skills. Strong stakeholder coordination and collaboration ability. Good technical documentation and presentation skills. Ability to manage multiple priorities and work independently. Self-driven, proactive, and solution-oriented mindset. Strong learning attitude toward emerging technologies and digital transformation initiatives. Preferred Skills (Good to Have) Experience in manufacturing, EPC, infrastructure, or industrial environments. Exposure to cloud platforms such as: Microsoft Azure Amazon Web Services Knowledge of Python or scripting for analytics automation. Familiarity with ERP and enterprise digital systems integration. Understanding of modern data engineering and business intelligence architecture. Exposure to AI/ML frameworks and predictive analytics use cases.