Information and Intelligence Architect

Posted Yesterday
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2 Locations
In-Office or Remote
Expert/Leader
Software
The Role
Lead enterprise data architecture and governance for financial services. Design cloud-native data platforms, data lakes/warehouses, real-time processing, and analytics. Manage data engineering and BI teams, define data quality, mapping, consumption policies, and drive data-driven culture and migration automation.
Summary Generated by Built In

About Us:

Network International is the largest Financial Technology company in the Middle East and Africa. Payments is our core business where we provide services in more than 50 countries – UAE, Jordan, South Africa, Egypt are some of our key markets. Apart from payments, we provide services on Data and Insights, Lending, Insurance, Risk Solutions, etc. Our core customers are businesses at every scale and segment, though recently we have been growing in the direct-to-consumer card segment as well.

Our EVP:

At Network International, we always stay ahead. . In the fast-paced world of financial services, we thrive on innovation, agility, and purposeful collaboration. We invest first in our people, empowering you to make bold decisions, learn fast, and grow your expertise alongside industry leaders. Here, solving complex problems means more than using cutting-edge technology; it’s about creating meaningful value for our customers, together. We foster a culture where trust, accountability, and achievement go hand in hand—because success isn’t just a goal; it’s how we work, every day, as one team.

About The Role:

We are seeking to hire for an Information and Intelligence Architect to lead the development of data architecture and contribute to the data management strategies, implementing and managing data governance processes to foster a data-driven decision-making culture. 

The incumbent is required to have an in-depth understanding of data entities and reference data models of Financial Services, including payment & payment related value-added services, domains. In addition, data literacy should have proven, including the ability to understand, describe and analyze business use cases, data sources and management concepts.

Responsibilities

Key Responsibilities:

  • Design scalable and efficient data architectures that support business goals, including data warehousing, data lakes, and real-time data processing, integration and automation outcomes.
  • Oversee all data-related activities, including the enterprise data platform, business intelligence tools and data-sharing capabilities.
  • Fosters value creation from data assets, and mature the Department's evidence-based, data-driven decision-making culture. 
  • Provide leadership and management of Data Engineers and Business Intelligence Developers.
  • Establish Data Architecture Principles, council, operating Model, Retention Policy.
  • Institute a programmatic approach for enterprise information management to identify, prioritize and execute data and analytic initiatives with clear line of sight to enterprise strategies and business outcomes.
  • Enforces adherence to architectural standards/principles, product-specific guidelines, usability design standards, etc.
  • Performs regular maturity assessments to ensure the delivery of the data strategy and track progress of data initiatives.
  • Innovate with and expand the organization's research and analytics offerings, emerging analytical approaches, skills and technologies.
  • Define Data Quality (DQ) Scorecard with DQ thresholds, Plan for rehearsal runs.
  • Define data relationships, source to target mapping, auto recon reports, Meta data tagging & relationship mapping.
  • Document business rules, approach for anomaly detection and handling, Outlier definitions and correction.
  • Define speed to market strategy for migration with automation like ETL, replication, virtualization, and virtual data analyst.
  • Define Data Consumption Patterns Policies, role-based access controls, regulatory compliance requirements.
  • Collaborates closely with key business partners to determine data requirements and to create a culture that manages data as an enterprise asset.
Qualifications

Key Requirements:

  • Bachelor’s Degree in Computer Information Systems / Computer Science.
  • 20 years of experience in Data Strategy, Data Enterprise Architecture, AI and Analytics Design and Implementation.
  • Deep understanding and experience designing using Cloud native data tool capability - Data Integration / ETL, Database Migration, Application Integration / Workflow Object Storage / Data Lake, Data Lake Governance,  Data Warehouse SQL/Relational DB,  Real-Time Streaming,  Managed Kafka,  Serverless Data Processing, Big Data Processing Search & Log Analytics,  Business Intelligence / Visualization,  Machine Learning Platform, AutoML, ML Dev Environment, Vision (Image/Video) Speech-to-Text & Text-to-Speech Translation, Data Management/Governance, Text Analytics & NLP Conversational, AI Document, AI Search with Semantic/Vector in both AWS, Azure and other hyper scalars. 
  • Prior experience in defining Data governance strategy, Data Discovery & Profiling Strategy, Data Quality Validation Strategies, Data Mapping Approach, Data Cleansing Approaches, Data Migration Automation Strategies, Data Security Strategy.
  • Experience with industry reference data model.
  • Experience in cloud native Data & Information Services in Cloud.
  • Highly developed verbal and interpersonal skills with the ability to build productive relationships and capability of communicating technical concepts to diverse stakeholders at all levels.

Skills Required

  • Bachelor's Degree in Computer Information Systems or Computer Science
  • 20 years of experience in Data Strategy, Data Enterprise Architecture, AI and Analytics design and implementation
  • Deep experience with cloud-native data capabilities across AWS and Azure: ETL, database migration, object storage, data lake governance, data warehouse, real-time streaming, managed Kafka, serverless processing, big data, search and log analytics
  • Experience defining Data Governance, Data Discovery & Profiling, Data Quality validation, Data Mapping, Data Cleansing, and Data Migration automation strategies
  • Experience with industry reference data models (financial services, payments domain)
  • Experience with machine learning platforms and ML workflows including AutoML, ML dev environments, NLP, computer vision, speech-to-text and semantic/vector search
  • Proven ability to lead and manage Data Engineers and Business Intelligence Developers
  • Strong verbal and interpersonal skills to communicate technical concepts to diverse stakeholders
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The Company
HQ: Austin, TX
8,275 Employees
Year Founded: 1976

What We Do

At NI, we Engineer Ambitiously. We celebrate creative problem solving. And we take our customer relationships to heart. We believe in the power and potential of making connections—between people, ideas, and technology. In fact, connection is central to everything we do. We constantly challenge ourselves to find those connections because that’s what creates a path forward. This means bringing the right people together to build solutions that make a difference. It means combining fresh perspectives with new technologies to turn your vision into reality. For more than four decades, we’ve set the standard in automated test and automated measurement systems. We’re proud to partner with the talented engineers and enterprises using our systems to solve the world’s most pressing technology challenges and build better businesses. From data and automation to research and validation, our tailored, software-connected approach is rooted in helping you engineer what’s next. As your trusted partner, we’re committed to helping you set your goals higher and reach them sooner. We’re here for you, for each other, and for the next generation of innovators who think bigger, aim higher, and go faster. Let’s Engineer Ambitiously.

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