Data Project Manager

7 - 11 years

0 Lacs

Posted:14 hours ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

As a results-driven Data Project Manager (PM) in a regulated banking environment, your role involves leading data initiatives using Databricks and Confluent Kafka. You will oversee end-to-end delivery of complex data transformation projects aligned with business and regulatory requirements. - Lead planning, execution, and delivery of enterprise data projects - Develop detailed project plans, delivery roadmaps, and work breakdown structures - Ensure resource allocation, budgeting, and adherence to timelines and quality standards Collaboration with data engineers, architects, business analysts, and platform teams is crucial. You will act as the primary liaison between business units, technology teams, and vendors, facilitating updates, meetings, and escalations. - Manage solution delivery on Databricks for data processing, ML pipelines, and analytics - Oversee real-time data streaming pipelines via Confluent Kafka - Ensure alignment with data governance, security, and regulatory frameworks Risk and compliance management are key aspects. You will ensure regulatory reporting data flows comply with financial standards and manage controls and audit requirements. Qualifications Required: - 7+ years of Project Management experience in banking or financial services - Proven experience in leading data platform projects - Strong understanding of data architecture, pipelines, and streaming technologies - Experience in managing cross-functional teams - Proficiency in Agile/Scrum and Waterfall methodologies Technical exposure to Databricks, Confluent Kafka, Azure/AWS Cloud Platforms, integration tools, CI/CD pipelines, and Oracle ERP Implementation is expected. Preferred qualifications include PMP/Prince2/Scrum Master certification and familiarity with regulatory frameworks. The ideal candidate will hold a Bachelors or Masters degree in Computer Science, Information Systems, Engineering, or related field. Key performance indicators include on-time, on-budget delivery, uptime of data pipelines, user satisfaction, and compliance with regulatory milestones.,

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