Data Architect

Openkyber

Job Title: Director, Data Management/Data Warehousing Solutions & AI Location: West Los Angles. CA Type: Temp to Hire Job Description: Client is looking for talented professionals to join them in bringing smart money management and payment solutions to everyone's fingertips. This position is classified as structured hybrid with an expectation of a minimum of three (3) days per week working in the office and flexibility to work remotely on the remaining days. On-site expectations may evolve over time to support business needs, with clear communication provided in advance. High Level Overview: Client is seeking a strategic and execution-focused Engineering Leader to lead the enterprise-wide data warehousing practice. This role will be responsible for leading the engineering aspect of data warehouse initiatives across all business units in terms of design, development and quality making sure the practice adheres to data governance. This position also leads the Data Governance practice and AI drive in the data spaces leveraging AWS Redshift, Informatica and Claude AI. It also defines data security and adheres to compliance rigors across data needs for all business units. You will partner closely with Technology, Risk, Compliance, and Product teams to drive data quality, lineage, and stewardship initiatives that support regulatory obligations and business growth. Key Responsibilities Lead the design, development and optimization of data warehouse solutions using AWS Redshift Define and execute the enterprise data strategy, architecture roadmap and modernization initiatives. Architecting and maintaining Operational data stores (ODS), Enterprise Data Warehouse (EDW) and associated data intelligence environments including data lakes, data marts, and metadata repositories. Designing and implementing high-performance data movement pipelines using multiple ETL tools (Informatica, Azure Data Factory, SQL Packages, etc.) with batch and real-time event data streams leveraging Informatica IDMC Ensure high availability, performance tuning, Scalability and reliability of data platforms and pipelines. Developing scalable and re-usable frameworks for ingestion of structured and semi-structured data; and implementing various large-scale settlement and reconciliation frameworks. Designing and creating data architecture and data flow diagrams and collaborating with peers to translate requirements into logical and physical data models. Ensures data warehouse features and capabilities are incorporated into data model designs to optimize performance, resiliency, and scalability. Delivering and presenting proofs of concept to of key technology components to project stakeholders and internal technology leaders. Leading and coordinating the design and operationalization of Data Governance capabilities like data lineage, data catalog, data quality, etc. Problem-solving of Data warehouse and ODS application issues and production errors, including high level critical production issues that require immediate attention. Write, test and produce production grade ETL data pipeline code in financial services without relying on testing by other groups. Implement intelligent testing frameworks that auto-generate test cases, predict bugs, and enable self-healing. Leads the creation of test strategy, test planning, and test execution related to all aspects of testing like functional, integration, systems, end-to-end testing, accessibility, database validations, and automation. Integrate test suites into CI/CD pipelines (Jenkins, Github). Metadata & Lineage Management: Oversee the implementation of tools and processes for metadata capture, data lineage tracking, and cataloging. Ensures data quality, completeness and consistency through carious quality checks and monitoring. Lead data governance rigors related to data practice in the company establishing data governance framework, policies and procedures Maintain documents related to data mapping and logic Partner with Data Analytics team, business and compliance teams to ensure adherence to regulatory requirements, data privacy and security standards Lead governance initiatives related to AI model usage, ethical AI practices and responsible on data utilization Partner with business and business teams driving generative AI initiatives. Evaluate and implement AI driven data management capabilities including automation, data classification and governance., Lead and mentor a large team of data engineering team Partner with executive leadership and business stakeholders to align data initiatives with strategic projects. Manage vendor relationships with AWS and Informatica, Project budgets and technology evaluations. Cross-Functional Leadership: Partner with Finance, HR, and Product to ensure data governance supports cost optimization, internal mobility, and product alignment goals Change Management: Strengthen compliance oversight and accountability over change management processes impacting data Enterprise Data Security: Partners with CISO and develop measures to protect sensitive customer data from unauthorized access or breaches. Required Qualifications Bachelors and/or master s degree in computer science, Computer Engineering or related field preferred. 10+ years of experience in enterprise Datawarehouse, data engineering or analytics platforms 5+ years in leadership or management roles overseeing enterprise data teams Strong hands-on experience with AWS Redshift Informatica IDMC Cloud based ETL/ELT architecture SQL Optimization Data Lineage Data Quality Experience in implementing data governance programs Strong understanding of Data Modeling Metadata Management Data Quality Frameworks Data Security and compliance standards Excellent Communication, executive stakeholder management skills and the ability to navigate relationships across business units. 3+ years of development experience with Python scripting experience. Knowledge of data governance, security, and compliance standards (e.g., SOC 2, PCI DSS). Demonstrated expertise in performance tuning in various DB environments with large volumes of data. Familiarity with CI/CD pipelines (e.g., Jenkins, GitHub Actions) and infrastructure-as-code tools. Expertise in understanding complex business needs, analyzing, designing, and developing solutions. Experience with metadata management, data lineage tools, and data quality frameworks. Deep understanding of regulatory frameworks (e.g., FRB, BSA/AML, UDAAP). Familiarity with cloud platforms (AWS, Azure) and open-source governance. Preferred Qualifications Financial technology domain knowledge Microsoft Azure Data Engineer or other cloud certifications
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Vacancy posted 2 days ago

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