Senior Data Engineer

Job description [Hybrid 2 days/week] Skill & Experience Mandatory Skills: GenAI Exposure, Data Modelling, Database Development, Data Warehouse Management, Data Strategy Development, End to end Data Architecture, Virtualization and Consumption layer expertise Developing and maintaining data pipelines for efficient data extraction, transformation, and loading (ETL) processes. Designing and optimizing data storage solutions, including data warehouses and data lakes. Ensuring data quality and integrity through data validation, cleansing, and error handling. Collaborating with data analysts, data architects, and software engineers to understand data requirements and deliver relevant data sets (e.g., for business intelligence). Implementing data security measures and access controls to protect sensitive information. Automating and improving data processes and workflows for scalability and efficiency. Monitoring data infrastructure for performance and reliability to address issues promptly. Keeping abreast of industry trends and emerging technologies in data engineering. Documenting data pipelines, processes, and best practices for knowledge sharing. Participating in data governance and compliance efforts to meet regulatory requirements. Providing technical support and mentoring to junior data engineers, if applicable. Continuously optimizing data architecture to support the company's evolving data needs. Collaborating with cross-functional teams to drive data-driven decision-making within the organization. Role: Data Engineer Industry Type: IT Services & Consulting Department: Engineering - Software & QA Employment Type: Full Time, Permanent Role Category: Software Development Education UG: Any Graduate PG: Any Postgraduate Doctorate: Doctorate Not Required Key Skills Skills highlighted with ‘‘ are preferred keyskills Data Engineering GenAIData Strategydata validationData modelingData Warehouse ManagementETLdatabase development