Data Engineering Manager

• Lead discussions with business users and stakeholders to solicit and document requirements for data projects, including data usage, master data management, and AI initiatives.
• Translate business needs into clear, actionable technical specifications and work breakdowns.
• Lead sprint ceremonies and manage project roadmaps to drive on-time, on-budget delivery
• Ensuring clear visibility into project milestones and resource utilization
• Proactively identify and remove obstacles by coordinating with stakeholders and ensuring the team has clear direction, resources, and support to maintain delivery momentum
• Lead the design, development, and optimization of scalable data pipelines, Master Data Management processes, and data services.
• Define robust data models and implement data quality checks along with governance frameworks.
• Encourage continuous learning by assigning real-world projects and case studies, then guiding reflective debriefs to reinforce lessons and foster independent problem-solving
• Facilitate hands-on workshops and knowledge-sharing sessions to strengthen technical competencies and promote best practices across data operations
• Establish and document best-practice run-books, decision logs, and process playbooks.
• Identify and implement process enhancements, enforce CI/CD standards for data workflows, and maintain compliance with data-security and regulatory requirements.

• Experience in Data Engineering, Data Operations or closely related roles
• Experience in leading requirements gathering sessions and translating business needs into technical specifications.
• Strong proficiency in data management practices, including creating data dictionaries and designing data models.
• Experience building and operating large scale data lake and data warehouse.
• Experience with Hadoop ecosystem and big data tools, including Spark and Kafka
• Experience with stream-processing systems including Spark-Streaming
• Hands-on experience with UML and data specification development.
• Experience with Agile & DevOps Practices would be advantageous
• Knowledge in Utilities data standard such as IEC Common Information Model would be advantageous
• Experience in AI and machine learning projects would be advantageous.
• Domain knowledge in Utilities sector would be advantageous
• Experience in Data Fabric and/or Data Mesh Architecture would be advantageous
• Experience in Open Data-Lakehouse would be advantageous
• Excellent communication and interpersonal skills, with the ability to convey complex technical plans into actionable updates.
• Strong analytical and problem-solving abilities, with keen attention to detail.
• Skilled in project-management tools and methodologies; uses data-driven insights to track progress, forecast resource needs, and inform decision-making

SP Group