Manager, Data Governance

**Take your Career to the next Level with MEVOTECH.**

**JOB PURPOSE**

Reporting directly to the Director Enterprise Architecture, the Manager, Data Governance will be responsible for managing and optimizing our data warehouse infrastructure, ensuring its reliability, scalability, and efficiency. This individual will be working closely with our finance and data analysts, and will play a key role in designing, implementing, and maintaining data warehouse solutions that support our organization's data-driven initiatives. This position requires a strong understanding of data warehousing principles, experience with relevant technologies, and the ability to collaborate effectively with cross-functional teams. This individual will play an integral role in upholding and overseeing the ongoing maintenance, optimization, and management of our database infrastructure. This role will encompass tasks such as ensuring data integrity, implementing performance enhancements, managing access controls, and overseeing backups and disaster recovery procedures.

**KEY DUTIES AND RESPONSIBILITIES**

**Data Integration, Analysis and Management**
- Implement robust ETL (Extract, Transform, Load) processes to integrate data from various sources into the data warehouse.
- Ensure data quality, consistency, and integrity through data validation, cleansing, and normalization techniques.
- Optimize data warehouse performance by fine-tuning queries, indexes, and database configurations.
- Scale data infrastructure to accommodate growing data volumes and evolving analytical needs while maintaining performance and reliability.
- Implement caching mechanisms and data partitioning strategies to improve query performance and resource utilization.
- Develop interactive dashboards and visualizations using tools like Tableau and Power BI

**Database Administration**
- Install, configure, and maintain database management systems (DBMS), ensuring optimal performance and reliability.
- Implement backup and recovery strategies to protect against data loss and minimize downtime in case of system failures or disasters.
- Monitor database performance metrics and system health indicators, identifying and addressing issues to maintain data warehouse availability and performance.

**AI Model Development and Co-Pilot**
- Experiment with various AI and machine learning models to extract preliminary insights, identify patterns, and explore predictive capabilities within the initial datasets.
- Work closely with data owners to prototype AI models using techniques such as regression, classification, clustering, and shallow learning algorithms.
- Iterate on model development based on feedback, performance evaluation, and early-stage experimentation to refine the approach.
- Deploy AI models into production environments and integrate them with existing systems for real-time data analysis and decision-making.
- Provide support and assistance for the rollout and implementation of Microsoft Co-Pilot, leveraging its AI capabilities, across the organization.
- Ensure continuous user support and address any issues or concerns promptly, specifically focusing on optimizing AI-driven workflows.
- Monitor AI performance metrics, analyze data insights, and collaborate with the IT, Finance and Forecasting team to refine AI algorithms and enhance Co-Pilot's overall effectiveness.

**Data Governance and Compliance**
- Establish data governance frameworks and policies to ensure data quality, security, and regulatory compliance.
- Define data access controls, encryption standards, and audit trails to protect sensitive information and mitigate risks.
- Conduct regular audits and assessments to monitor compliance with data governance standards and industry regulations.

**Collaboration and Knowledge Sharing**
- Collaborate with cross-functional teams including data analyst, business analysts, and IT professionals to understand business requirements and deliver data-driven solutions.
- Share expertise and best practices with team members through training sessions, documentation, and knowledge sharing sessions.
- Stay abreast of emerging technologies, industry trends, and best practices in data warehousing, AI, and analytics to drive innovation and continuous improvement.

**QUALIFICATIONS, SKILLS, AND EDUCATIONAL REQUIREMENTS**
- Bachelor's degree in computer science, information systems, or a related field; or equivalent work experience.
- Proven experience in designing and implementing an operational production grade large-scale data solution on Snowflake.
- Proficiency in SQL and experience with relational database management systems (e.g. SQL Server, Informix).
- Familiarity with ETL tools and processes such as SSIS and Azure Data Factory.
- Familiarity with AI and machine learning concepts and frameworks, including supervised and unsupervised learning, regression analysis, and neural networks.
- Experience with programming languages such as Python, R, or Java for data analys