Technical Manager/ Data Project Manager (Lead Data engineer)

Responsibilities • Lead and manage large-scale Data Engineering and Data Modernization projects. • Drive end-to-end delivery of Data Lake build and migration initiatives. • Lead PySpark migration and optimization projects, ensuring performance and scalability. • Design and implement modern data architectures, including Data Lakes, Data Warehouses, and Lakehouse solutions. • Collaborate with business stakeholders, architects, and engineering teams to define data strategies and roadmaps. • Provide technical leadership and mentorship to Data Engineers and Developers. • Ensure best practices around data governance, security and compliance, and performance optimization. • Lead data platform modernization initiatives across cloud environments. • Review solution designs, architecture documents, and implementation approaches. • Manage project planning, resource allocation, risks, and delivery timelines. • Drive Agile delivery and ensure successful project execution. Requirements • 8+ years of experience in Data Engineering and Data Platform delivery. • Minimum 3+ years of experience in a Technical Manager or Lead role. • Proven experience in delivering: • Data Lake implementation projects • Data Lake migration programs • PySpark migration projects • Large-scale data transformation initiatives Technical Skills • Strong expertise in: • Python • PySpark • Spark SQL • SQL • ETL/ELT frameworks • Experience with: • Hadoop ecosystem • Data Lakes and Lakehouse architectures • Distributed data processing frameworks • Strong understanding of: • Data modeling • Data integration patterns • Batch and real-time processing • Experience with cloud platforms such as: • AWS • Azure • GCP • Hands‑on experience with: • Data migration strategies • Performance tuning and optimisation • CI/CD and DevOps practices for data platforms Must Have • Hands‑on experience in managing Data projects end-to-end — effort estimation, scoping, project plan, timelines, team allocation, stakeholder management. • Hands‑on experience with modern Data technologies like PySpark, SQL, CML, Python on any cloud; preferred GCP. • Transform business requirements into Data solutions, manage risks, issues and dependencies. #J-18808-Ljbffr