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- Work with stakeholders to define requirements, constraints, and goals
- Stay current on changes within the industry and communicate any alignment with Bank initiatives to interested parties
- Understand and adopt all relevant policies, standards, and procedures
- Make presentations to technical and non-technical stakeholders
- Establish standards, procedures, guidelines, and best practices related to the Data Lake and ML programs
- Lead discussions about short term tactical fixes vs. long term strategic goals to prioritize work
- Conduct research and remain current with the latest data technologies and solutions in support of future data management procurement efforts of the BI/EDW architecture
- Consult resident and external subject matter experts to curate informed decisions
- Liaise with vendors for the procurement of new technologies and services
- Prepare budget proposals and operational expenditure statements
- Curate documentation related to architecture, infrastructure, and disaster recovery; make recommendations for improvements and/or alternatives
- Assist the business with machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Delegate responsibilities to team members as appropriate
- Provide mentoring, training, and guidance to members of the team
- Promote and enforce standards, procedures, guidelines, and best practices
- Manage the deployment, monitoring, maintenance, development, upgrade, and support of the Data Lake and enterprise data infrastructure, including data architecture, data integration, high availability, security, and data privacy
- Ensure the efficient utilization of data resources
- Approve purchase of equipment and supplies to meet operational requirements of the business
- Analyze existing operations and make recommendations for the improvement and growth of the BI/EDW architecture
- 4 year college degree in information technology or equivalent experience
- 5+ years of database and data management experience.
- Extensive experience working within an agile/SCRUM environment
- Ability to leverage a broad stack of technologies — DataBricks, FiveTran, Python, AWS, SageMaker, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
- An ability to adopt new ways of working and embrace new technologies and techniques
- Experience building or managing an enterprise Data Lake and/or ML program
- FiveTran, DataBricks, AWS or other related data certifications are highly preferred