We prefer a hybrid candidate located in NYC but are also open to someone who is 100% remote. 

Our client is a PE-backed consumer-focused company in the Financial Services space that is gearing up for long-term strategic initiatives centered around the integration of systems/data. They are a conglomerate of many different businesses acquired over the years and are looking to bring everything onto a common platform which will require a plan around Data. This role will be a key cog in accomplishing this and will have tremendous revenue along with business impact. 

Responsibilities: 

• Developing and implementing an overall organizational data strategy that is in line with business processes. The strategy consists of working with data modeler to ensure optimal data model designs, database development standards, implementation, and management of transaction, ODS and Analytical platform
• Identifying data sources, both internal and external, and working out a plan for data management that is aligned with organizational data strategy.
• Coordinating and collaborating with cross-functional teams, stakeholders, and vendors for the smooth functioning of the enterprise data system.
• Managing end-to-end data architecture, from selecting the platform, designing the technical architecture, and developing the application to finally testing and implementing the proposed solution.
• Defining and managing the flow of data and dissemination of information within the organization.
• Integrating technical functionality, ensuring data accessibility, accuracy, and security.
• Conducting a continuous audit of data management system performance, refine whenever required, and report immediately any breach or loopholes to the stakeholders.

 Requirements: 

• 10+ years experience. Financial Services industry experience preferred
• Experience with modern tools/technologies (E.G. Snowflake, Databricks, etc)
• Knowledge of systems development, including system development life cycle, project management approaches and requirements, design and testing techniques
• Proficiency in data modeling and design, including SQL development and database administration
• Understanding of predictive modeling, NLP, ML, and text analysis
• Ability to implement common data management and reporting technologies and the basics of columnar and NoSQL databases, data visualization, unstructured data, and predictive analytics.
• Data mining, visualization, and Machine Learning skills
• Knowledge of programming languages Python, C/C++, Java, and Perl
• Team and stakeholder collaboration is one of the soft skills a data architect must have because they need to coordinate and collaborate with users, system designers, and developers in their day-to-day functions.
• Effective communication and leadership qualities.