3 Data Architects Jobs

As a highly skilled Data Governance Developer with expertise in Microsoft Purview and metadata management, you will be responsible for supporting enterprise-wide data governance initiatives. Your role will involve implementing scalable data governance solutions, particularly in the investment banking or financial services domain, and ensuring the enforcement of data policies, standards, and lineage across cloud environments. You will lead and support the complete implementation of Microsoft Purview, including tasks such as configuration, scanning, and API integrations. Additionally, you will design and manage enterprise business glossaries, data classifications, metadata lineage, and technical/business metadata association. Your responsibilities will also include configuring and automating metadata ingestion pipelines from various sources in Azure, AWS, and GCP environments. Collaboration with data stewards, architects, and platform teams will be essential to define and maintain data governance standards and processes. You will be expected to ensure compliance with cloud security, regulatory standards, and data governance frameworks. Monitoring metadata quality, lineage visibility, and data catalog health through regular audits and improvements will also be part of your duties. Furthermore, you will provide technical guidance on Purview APIs and their integration with AI/ML data pipelines. Your contribution to data governance frameworks in Agile project delivery and DevOps cultures will be crucial for the success of the data governance initiatives. To be successful in this role, you should have at least 5 years of experience in data governance, metadata management, or data cataloging in enterprise environments. You must possess a minimum of 12 years of hands-on experience with Microsoft Purview, including at least one end-to-end implementation. Proficiency in Purview API usage, resource scanning, classification, and metadata mapping is required. A strong understanding of data lineage, data dictionaries, and glossary management is essential. Previous experience in investment banking, capital markets, or regulated financial environments would be highly advantageous. Familiarity with cloud platforms such as Azure, AWS, and GCP, especially in data services and governance controls, is preferred. Knowledge of AI/ML-enabled metadata automation and intelligent classification is considered a plus. Excellent interpersonal and communication skills are necessary to engage with both technical and business stakeholders effectively. Holding Microsoft certifications in Azure Data Engineer, Security Engineer, or Purview will be a strong advantage in this role.,

A career within Actuarial Services will provide you with the opportunity to contribute general insurance advice and consulting services to clients such as insurers, banks, regulators, and third-party administrators. You will provide advice covering solvency, economic capital, risk management, mergers and acquisitions, company restructuring and risk control, financial modeling, underwriting, new legislation, and the efficiency of claims or reporting processes. Your role may involve analyzing the impact that new regulations will have on an insurance company's balance sheet or revising business projections to ensure adequate reserves. To stand out and ensure a successful future in a constantly changing world, each individual at PwC needs to be a purpose-led and values-driven leader at every level. The PwC Professional, our global leadership development framework, sets clear expectations across lines, geographies, and career paths. It emphasizes the skills required for success and career progression in the present and future. **Responsibilities:** As a Senior Associate, working as part of a problem-solving team at PwC, your responsibilities include but are not limited to: - Developing self-awareness, addressing development areas, and leveraging feedback and reflection. - Delegating tasks to provide growth opportunities for others, coaching them to achieve results. - Demonstrating critical thinking and structuring solutions for complex business problems. - Utilizing various tools and techniques to extract insights from industry trends. - Reviewing work for quality, accuracy, and relevance, including that of colleagues. - Making informed decisions on tool usage and explaining the rationale behind choices. - Embracing diverse opportunities to gain exposure to different situations and perspectives. - Communicating effectively and influencing others in a structured manner. - Adapting behavior to build strong relationships and upholding ethical standards. - Contributing to the development of AI solutions, including prompt engineering, retrieval-augmented generation, fine-tuning, and multi-agent systems. - Applying econometric modeling techniques like GLMs, time series analysis, and semi-parametric models. - Using machine learning models such as XGBoost, random forests, and support vector machines. - Ensuring compliance with model-related regulatory requirements during model development, validation, and monitoring. - Proficiency in programming languages like Python, R, Databricks, and React. - Enforcing DevOps best practices including version control, CI/CD, test automation, and collaboration. - Designing, developing, and deploying AI models in real-world client environments. - Monitoring AI trends and supporting project delivery to enhance business processes and decision-making. - Collaborating with cross-functional teams to deliver high-quality solutions aligned with client needs. - Supporting business development efforts and internal GenAI assets to grow the firm's practice. **Qualifications:** **Minimum Educational Qualifications:** - A degree in statistics, mathematics, electrical engineering, physics, econometrics, computer science, or related technical fields. **Credentials - Good To Have:** - A master's degree or PhD in a related field from a premium institute is preferred but not required. **Minimum Years of Experience Requirement (Credential):** - 3-4 years of relevant experience.,

Roles & Responsibilities: Assist with the data platform blueprint and design. Collaborate with Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Develop and maintain data platform components. Contribute to the overall success of the project. Professional & Technical Skills: Proficiency in Databricks Unified Data Analytics Platform. Strong understanding of statistical analysis and machine learning algorithms. Experience with data visualization tools such as Tableau or Power BI. Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.