Data Management Manager

Job Summary

We are seeking a strategic and hands-on Manager of Data Management to lead a high-performing team of 40-50 data professionals responsible for the design, operation, governance, and modernization of enterprise data platforms. Reporting to the Director, Data Tower, this role will oversee legacy data environments while driving the organization's transition to modern Data Lake and cloud-based architectures. The ideal candidate combines strong leadership capabilities with deep expertise in enterprise data management, governance, cloud platforms, and large-scale data transformation initiatives.

Key Responsibilities

1. Lead, mentor, and develop a team of 40-50 data engineers, analysts, and data operations professionals.
2. Establish team goals, KPIs, performance expectations, and career development plans.
3. Foster a culture of accountability, collaboration, innovation, and continuous improvement.
4. Manage workforce planning, resource allocation, hiring, and team capacity.
5. Partner with Data Tower leadership to develop and enforce enterprise data governance standards and policies.

Dri ve improvements in:

1. Data Quality
2. Data Lineage
3. Data Cataloging
4. Master Data Management (MDM)
5. Ensure compliance with data governance, regulatory, security, and privacy requirements.
6. Define and manage service level agreements (SLAs) and service level indicators (SLIs) for enterprise data platforms.
7. Implement monitoring, alerting, incident management, and operational support processes.
8. Optimize platform performance, scalability, availability, reliability, and operational costs.
9. Collaborate with Technology, Product, Enterprise Architecture, Engineering, and business stakeholders to align enterprise data strategy with organizational objectives.
10. Provide regular updates to senior leadership regarding project status, risks, and strategic initiatives.
11. Lead enterprise data modernization efforts by designing and implementing modern Data Lake and Lakehouse architectures.
12. Support migration of legacy data pipelines to cloud-native data platforms.
13. Establish best practices for:
14. Data Ingestion
15. Data Transformation
16. Streaming
17. Data Storage
18. Promote adoption of scalable, cloud-native data services, engineering standards, and operational best practices.

Required Qualification s

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field, or equivalent professional experience.
• 8+ years of experience in Data Management, Data Engineering, or Data Operations.
• 5+ years of experience leading large technical teams, preferably managing 40 or more team members.
• Strong experience with enterprise data platforms, including:
• Microsoft SQL Server
• Oracle
• Teradata
• Hands-on experience with modern data architectures, including Data Lakes, Lakehouses, and cloud-based data platforms.
• Proven experience leading enterprise data modernization or cloud migration initiatives.
• Strong understanding of:
• ETL/ELT processes
• Data Modeling
• Distributed Data Systems
• Experience with one or more major cloud platforms:
• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud Platform (GCP)
• Strong leadership, project management, stakeholder management, and organizational skills.
• Excellent communication, analytical, and problem-solving abilities.

Preferred Qualifications

1. Experience with:
2. Databricks
3. Snowflake
4. Azure Synapse Analytics
5. Hadoop Ecosystem
6. Knowledge of Master Data Management (MDM) tools, including Ab Initio.
7. Experience with real-time data streaming technologies, including:
8. Apache Kafka
9. Spark Streaming
10. Familiarity with DevOps and DataOps methodologies.
11. Experience implementing enterprise data governance frameworks.
12. Experience leading cloud-native data platform transformations.
13. Hybrid work experience supporting globally distributed teams.

Certifications

1. Microsoft Azure Certifications - Preferred.
2. AWS Certifications - Preferred.
3. Google Cloud Professional Certifications - Preferred.
4. Snowflake Certifications - Preferred.
5. Databricks Certifications - Preferred.
6. Other cloud or enterprise data platform certifications - Preferred.