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Job Description
The Data Architect plays a pivotal role in shaping the enterprise data landscape. This position will be responsible forleading the design, development, and governance of scalable, secure, and high-quality enterprise data architecture that will support decision-making and strategic initiatives for all business units across the enterprise.
Job Description
The Data Architect plays a pivotal role in shaping the enterprise data landscape. This position will be responsible forleading the design, development, and governance of scalable, secure, and high-quality enterprise data architecture that will support decision-making and strategic initiatives for all business units across the enterprise.
This role will be instrumental in shaping how data is structured, accessed, and leveraged across the organization to drive business insights and operational efficiency. The Senior Data Architect will focus on Data Lakehouse designs, advanced analytics, and forward-looking AI/ML technologies. Additionally, this role will be a key member of the Solution Architecture team, providing an overall view of data architecture across solutions for the enterprise. The ideal candidate will have a strong background in data architecture, data engineering, and analytics, with a proven track record of successfully leading data implementations.
How You'll Make An Impact
- Drive Strategic Data Utilization: By designing and governing enterprise-wide data architecture, the Data Architect will enable our client to structure and access data in ways that unlock business insights and improve operational efficiency.
- Ensure Scalable and Compliant Data Infrastructure: Through the integration of modern data technologies and adherence to privacy and security standards (e.g., GDPR, CCPA, SOC 2), this role ensures the data ecosystem is both scalable and compliant.
- Empower Cross-Functional Collaboration and Innovation: By partnering with teams across engineering, analytics, compliance, and business units, the Data Architect will align data systems with strategic goals, supporting initiatives in BI, AI/ML, and centralized data platforms.
- Design and maintain enterprise-wide data architecture aligned with business goals, operational efficiency, cyber security, and data safety standards in alignment with our clients regulatory requirements; including data models, data lakes, data warehouses, and real-time data pipelines.
- Participate in strategic planning for the organization, driving high-level technical direction and vision.
- Lead the data transformation from traditional data architectures to a modern data lakehouse architecture.
- Provide leadership to the technical team and colleagues; help lead effort to build target team structure.
- Provide architectural oversight and validation of conceptual, logical, and physical data models developed by the data modeling team, ensuring alignment with enterprise data architecture standards and strategic objectives.
- Lead the integration of data from multiple internal and external sources, ensuring consistency, accuracy, and quality across systems through close collaboration with cross-functional IT teams.
- Collaborate with cross-functional teams including data engineering, network and system operations, identity and access, analytics, compliance, and business stakeholders to align data architecture with business goals.
- Ensure data integration strategies support enterprise standards for high availability, scalability, security, and resilience.
- Continuously explore, evaluate, and recommend modern data technologies (e.g., cloud data platforms, Databricks, etc.) to enhance the enterprise data ecosystem.
- Collaborate with Data Governance and business units to understand their data needs and provide solutions.
- Communicate complex technical concepts to non-technical stakeholders in a clear and concise manner.
- Ensure compliance with data privacy and security standards (e.g., PII, SOX, SOC 2).
- Support the development and continuous enhancement of our clients centralized data platform and contribute to the evolution of their data lakehouse and governance frameworks.
- Provide technical leadership and guidance on data architecture best practices and standards.
- Serve as the primary point of contact for data architecture across the enterprise.
- Work closely with data scientists and analysts to ensure data availability and quality for advanced analytics use cases.
- Foster a culture of data-driven decision-making across the organization.
- Provide architectural guidance and standardization for data warehousing, BI, and AI/ML initiatives.
- Stay current with emerging technologies and trends in data architecture, analytics, and AI/ML.
- Bachelors or Masters degree in Computer Science, Information Systems, or a related field.
- 10+ years of experience in data architecture, data engineering, or database design.
- Proven experience in leading data transformation initiatives.
- Deep expertise in Spark, Python, SQL, data modeling, and ETL/ELT pipeline strategy and optimization.
- Extensive experience with Data Lakehouse designs and advanced analytics.
- Hands-on experience with AI/ML technologies and their application in data architectures.
- Banking industry knowledge an added plus.
- Ability to work effectively in a fast-paced, dynamic environment where priorities can change quickly.
- Hands-on experience with cloud platforms (e.g., AWS, Azure, GCP) and tools like Snowflake, Databricks, or BigQuery.
- Strong understanding of financial data domains such as payments, lending, or capital markets.
- Strong understanding of data governance, security, and compliance frameworks.
- Familiarity with regulatory reporting and compliance in financial services.
- Experience with data cataloging tools and data governance frameworks.
- Knowledge of Python, Spark, or other data processing languages.
- Experience working in an Agile Scrum environment.
- Proven ability to partner with and challenge strategic implementation partner(s).
- Excellent communication and stakeholder management skills.
- Certifications in data architecture or related fields, including: Certified Data Management Professional (CDMP), AWS Certified Data Analytics, Google Cloud Professional Data Engineer, Databricks Certified Engineer.
- Experience with the Databricks platform is required.
Benefits: Medical Insurance, PTO, 401 (k) and more
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Job function
Engineering and Information TechnologyIndustries
Staffing and Recruiting
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