Data Architect

Key Responsibilities:
Will help lead the development and articulate long-term strategic goals for data architecture vision and establish data standards for Non-Financial Risk systems and processes
Will support the management of Clients resources, providing oversight, guidance and SME inputs.
Will coordinate between Non-Financial Risk business stakeholders and technical teams.
Develop and articulate long-term strategic goals for data architecture vision and establish data standards for enterprise systems.
Utilize various cloud technologies, including Azure, AWS, Google Cloud Platform, and data platforms like Databricks and Snowflake.
Conceptualize and create an end-to-end vision outlining the seamless flow of data through successive stages.
Institute processes for governing the identification, collection, and utilization of corporate metadata, ensuring accuracy and validity.
Implement methods and procedures for tracking data quality, completeness, redundancy, compliance, and continuous improvement.
Evaluate and determine governance, stewardship, and frameworks for effective data management across the enterprise.
Develop comprehensive strategies and plans for data capacity planning, data security, life cycle data management, scalability, backup, disaster recovery, business continuity, and archiving.
Identify potential areas for policy and procedure enhancements, initiating changes where required for optimal data management.
Formulate and maintain data models and establish policies and procedures for functional design.
Offer technical recommendations to senior managers and technical staff in the development and implementation of databases and documentation.
Stay informed about upgrades and emerging database technologies through continuous research.
Collaborate with project managers and business leaders on all projects involving enterprise data.
Document the data architecture and environment to ensure a current and accurate understanding of the overall data landscape.
Design and implement data solutions tailored to meet customer needs and specific use cases.
Provide thought leadership by recommending the most suitable technologies and solutions for various use cases, spanning from the application layer to infrastructure.

Basic Qualifications:
8 years of hands-on experience across Data Management, Data Engineering, Data Architecture
5 years of SQL, Python, and Excel experience
2 years of Financial Services experience (industry or FS management consulting)
2 years of Data Visualization experience (Power BI and/or Tableau)
2 years of experience managing an offshore team
2 years of experience with Cloud-based systems (Azure, AWS, or Google Cloud Platform)
2 years of Enterprise Data Architecture experience (such as end to data sourcing, pipeline ETL/ELT process, curation, data quality)
2 years of experience driving end-to-end technology solutions.
Ability to travel at least 25%.

Preferred Skills:
Possess certifications in AWS, Azure, and Google Cloud Platform to complement extensive hands-on experience.
Demonstrated expertise with certifications in Snowflake.
Hands-on experience with data science (AI/ML/Gen AI)
Hands-on experience with MDM, DQ, DG tools (e.g., Collibra, Informatica, Alteryx, Microsoft Purview, etc.)
Experience using R (or similar tools)
Valuable "Big 4" Management Consulting experience or exposure to multiple industries.
Undergraduate or graduate degree preferred.