As a
Data Architect, you will develop, implement, and manage robust data architecture
strategies and systems that meet the specialized needs of a financial institution. Guided by the
DAMA-DMBOK v2 framework, this role emphasizes data security, regulatory compliance, data
quality, metadata management, master data management, and the continuous advancement of
AI and machine learning solutions.
1. Banking-Specific Data Architecture Design and Management
o Develop and maintain data architectures tailored to various banking domains
(e.g., retail, transaction, investment banking, and risk management).
o Design high-performance data solutions capable of handling large volumes of
financial transactions and customer data.
o Ensure alignment with relevant financial regulations (e.g., Basel, GDPR, PCI-DSS)
and industry standards.
2. Data Governance and Compliance
o Implement and uphold data governance frameworks rooted in DAMA-DMBOK v2
principles.
o Oversee data accuracy, integrity, and adherence to financial industry standards
and regulations.
o Formulate and enforce policies for data privacy, security, and ethical data usage.
o Establish and guide metadata management strategies consistent with the bank’s
overall data strategy.
3. Leadership in Financial Data Management (Applicable for Lead Level Only)
o Direct and mentor teams of data architects, data modelers, and data mappers
specialized in financial systems.
o Champion the adoption of data warehousing, advanced analytics, and Business
Intelligence (BI) solutions, including AI and Generative AI.
o Foster a data-driven culture by advocating for insights-based decision-making at
all organizational levels.
4. Technology Integration and Innovation
o Work closely with IT Solutions Architecture and Enterprise Architecture teams to
ensure alignment of data strategies with broader organizational goals.
o Take ownership of technology selection for data platforms and collaborate with
technology teams to implement these solutions.
o Continually evaluate and integrate emerging technologies (AI, ML, Generative AI)
into the data architecture, ensuring performance and compliance.
o Oversee cloud migration and evaluate cloud-based data management solutions
(e.g., AWS, Azure, Snowflake, Databricks), ensuring they meet security and
regulatory mandates.
o Lead the architecture and design of AI, ML, data science, and generative AI
solutions to elevate the bank’s analytical and predictive capabilities.
o Stay current with new and upcoming trends in data practices, proactively
recommending improvements and innovations.
5. Project Management and Collaboration
o Collaborate with IT, Risk Management, Finance, and other departments to align
data architecture strategies with overarching business objectives.
o Lead and execute data architecture projects within budget and time constraints,
adhering to industry and internal standards.
o Serve as the primary liaison to external stakeholders, including regulatory bodies
and technology partners.