As a Data Governance Architect at Straive, you will play a crucial role in defining and leading enterprise-wide data governance strategies, designing governance architecture, and implementing tools like Informatica EDC/AXON, Collibra, Alation, MHUB, and other leading Data Governance platforms. Your primary responsibility will be to ensure data quality, consistency, and accessibility across various Enterprise platforms and business units. **Key Responsibilities:** - Design, develop, and maintain enterprise-wide data governance architecture frameworks and metadata models. - Establish data governance strategies, policies, standards, and procedures for compliance processes. - Conduct maturity assessments and change management efforts. - Evaluate and recommend Data Governance framework and tools to meet enterprise business needs. - Design and implement architectural patterns for data catalog, data quality, metadata management, data lineage, data security, and master data management (MDM) across various data platforms. - Create and manage data dictionaries, metadata repositories, and data catalogs. - Architect technical and business metadata workflows and govern glossary approvals and workflows. - Validate end-to-end lineage across multiple sources and targets. - Design and enforce rules for classification, access, retention, and sharing data techniques. - Analyze and define the enterprise business KPIs and validate data governance requirements. - Collaborate with Data Stewards to define technical specifications for data quality rules, validation checks, and KPIs reporting. - Collaborate with cross-functional teams to understand business requirements and translate them into technical specifications. - Ensure data compliance with relevant regulations like GDPR, HIPAA, CCPA, SOX, etc. - Excellent communication and ability to mentor and inspire teams. **Qualifications Required:** - Bachelor's/master's degree in information systems, Computer Science, or a related technical field. - Strong knowledge of data governance, architecture techniques, and methodologies with experience in data governance initiatives. - Minimum 7 years of experience in data governance architecture and implementation across business enterprises. - Hands-on experience in designing and implementing architectural patterns for data quality, metadata management, data lineage, data security, and master data management. - Strong expertise in Collibra including workflows, APIs, metadata integration, and policy automation. - Experience with ETL/ELT pipelines, data lineage capture, and data integration tools. - Proficiency in SQL, Python/Java for integration and automation. - Familiarity with data modeling (conceptual, logical, physical). - Proficiency in working with cloud platforms (AWS, Azure, or GCP). - Knowledge of big data technologies (Hadoop/Spark, etc.) and data visualization and BI tools. As a Data Governance Architect at Straive, you will be a part of a market-leading Content and Data Technology company, contributing to data services, subject matter expertise, and technology solutions across various domains. With a client-base spanning 30 countries worldwide, you will have the opportunity to work with a diverse and multi-geographical resource pool strategically located in eight countries. As a Data Governance Architect at Straive, you will play a crucial role in defining and leading enterprise-wide data governance strategies, designing governance architecture, and implementing tools like Informatica EDC/AXON, Collibra, Alation, MHUB, and other leading Data Governance platforms. Your primary responsibility will be to ensure data quality, consistency, and accessibility across various Enterprise platforms and business units. **Key Responsibilities:** - Design, develop, and maintain enterprise-wide data governance architecture frameworks and metadata models. - Establish data governance strategies, policies, standards, and procedures for compliance processes. - Conduct maturity assessments and change management efforts. - Evaluate and recommend Data Governance framework and tools to meet enterprise business needs. - Design and implement architectural patterns for data catalog, data quality, metadata management, data lineage, data security, and master data management (MDM) across various data platforms. - Create and manage data dictionaries, metadata repositories, and data catalogs. - Architect technical and business metadata workflows and govern glossary approvals and workflows. - Validate end-to-end lineage across multiple sources and targets. - Design and enforce rules for classification, access, retention, and sharing data techniques. - Analyze and define the enterprise business KPIs and validate data governance requirements. - Collaborate with Data Stewards to define technical specifications for data quality rules, validation checks, and KPIs reporting. - Collaborate with cross-functional teams to understand business requirements and transla
As a Data Analytics Specialist focusing on Fraud Prevention, your role will involve utilizing data analytics tools and methodologies to conduct detailed assessments and generate fraud rules and reports on various fraud trends, including Merchant Fraud, first-party, and third-party fraud. You will be responsible for investigating suspicious activities and transactions, identifying root causes, and devising strategies and statistical models to prevent future occurrences. Your duties will also include developing fraud rules on workflow systems, creating fraud reports for ongoing monitoring, and preparing reports and presentations outlining fraud risks, incidents, and mitigation strategies for management review. Additionally, you will collaborate with cross-functional teams such as risk management, operations, and compliance to enhance fraud prevention measures. It will be essential for you to stay updated on industry trends, regulatory changes, and best practices to continually strengthen fraud prevention strategies. Key Responsibilities: - Utilize data analytics tools and methodologies to conduct assessments and generate fraud rules and reports - Investigate suspicious activities and transactions, determine root causes, and develop prevention strategies - Develop fraud rules on workflow systems and generate reports for ongoing monitoring - Prepare reports and presentations outlining fraud risks, incidents, and mitigation strategies - Collaborate with cross-functional teams to enhance fraud prevention measures - Monitor industry trends, regulatory changes, and best practices for continuous improvement Qualifications Required: - Bachelor's degree in engineering, technology, computer science, or a related field - 10+ years of proven data analytics experience in fraud prevention, risk management, or a related field - Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance - Excellent communication and presentation skills with the ability to convey complex information clearly and concisely - Detail-oriented with a proactive mindset towards problem-solving and risk mitigation - Ability to work collaboratively in a cross-functional team environment As a Data Analytics Specialist focusing on Fraud Prevention, your role will involve utilizing data analytics tools and methodologies to conduct detailed assessments and generate fraud rules and reports on various fraud trends, including Merchant Fraud, first-party, and third-party fraud. You will be responsible for investigating suspicious activities and transactions, identifying root causes, and devising strategies and statistical models to prevent future occurrences. Your duties will also include developing fraud rules on workflow systems, creating fraud reports for ongoing monitoring, and preparing reports and presentations outlining fraud risks, incidents, and mitigation strategies for management review. Additionally, you will collaborate with cross-functional teams such as risk management, operations, and compliance to enhance fraud prevention measures. It will be essential for you to stay updated on industry trends, regulatory changes, and best practices to continually strengthen fraud prevention strategies. Key Responsibilities: - Utilize data analytics tools and methodologies to conduct assessments and generate fraud rules and reports - Investigate suspicious activities and transactions, determine root causes, and develop prevention strategies - Develop fraud rules on workflow systems and generate reports for ongoing monitoring - Prepare reports and presentations outlining fraud risks, incidents, and mitigation strategies - Collaborate with cross-functional teams to enhance fraud prevention measures - Monitor industry trends, regulatory changes, and best practices for continuous improvement Qualifications Required: - Bachelor's degree in engineering, technology, computer science, or a related field - 10+ years of proven data analytics experience in fraud prevention, risk management, or a related field - Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance - Excellent communication and presentation skills with the ability to convey complex information clearly and concisely - Detail-oriented with a proactive mindset towards problem-solving and risk mitigation - Ability to work collaboratively in a cross-functional team environment