• Own the architecture, implementation, and delivery of the Enterprise Data Warehouse (EDW) • Knowledgeable on middleware & ETL technologies and ability to partner with vendors to implement capabilities • Deep understanding of MDM technologies and how to integrate into an organizational operational processes • Translate business requirements into scalable data architecture and actionable technical plans • Define and enforce data standards, lineage, and attribute mapping across systems • Design logical and dimensional data models to support enterprise reporting and analytics • Build and maintain a comprehensive data dictionary and metadata repository • Conduct in-depth data analysis using SQL and other tools to validate and audit data quality • Ensure adherence to best practices in data governance, security, and performance optimization • Work closely with functional partners and IT business analysts to understand requirements and translate them into technical solutions • Communicate technical concepts clearly to both technical and non-technical audiences • Partner with other IT teams to ensure seamless integration across systems and platforms • Work independently and proactively in a fast-paced, deadline-driven environment

Role Description The [DATA FEED COORDINATOR] is responsible for coordinating the various components of Ylopo’s IDX data feed integrations, including compliance, billing, and reporting. This team member will correspond with various members of MLS boards and may interact with clients and/or brokers on occasion. This role will be email and phone based. This role reports to Erin Druskbasky [MLS Operations Manager]. - Manage IDX paperwork and reporting for Ylopo clients to ensure compliance with MLS boards - Maintain existing documentation and build new documentation (Google Sheets/Docs/Excel Spreadsheets) based on internal organization of MLS boards and their related IDX feeds - Review and report IDX feed technical issues to MLS boards and vendor contacts - Respond (via phone/email/text) to all client and/or MLS board requests in a timely manner (2 hour TAT) to provide a high level of customer support - Speak confidently and professionally with MLS board representatives, clients, and brokers - Complete special projects and outbound calls as needed - Serve as subject matter expert for Ylopo MLS/IDX data feed process - Learn the ins and outs of Ylopo product Qualifications - Previous experience in a support, administrative, or customer service role - Experience working with an enterprise CRM (Salesforce, Zoho, HubSpot) - Intermediate level knowledge of Excel or Google Sheets - Professional manner including a positive demeanor, trustworthy character - Consistent work habits and strong work ethic - Strong organizational skills and attention to detail - Ability to multitask, and work independently toward deadlines - Strong written and verbal communication skills, ability to work well in a small group setting - Ability to take initiative and see projects and tasks through to completion - Ability to understand and convey detailed information - Understanding of real estate and the real estate profession a plus, but not necessary Requirements - The processor should be 2.0ghz and above, Intel core 5/7 is highly required for both main and back-up hardware - RAM should be at least 16 GB with 100 GB Free disk space - A headset with the noise-canceling feature - 20 Mbps & up wired connection for the main internet service - Strictly no USB Sticks allowed for backup internet connection Benefits - A commitment to personal development - Guidance and support at a high level through interfacing with our Executive Team to prioritize goals as a company - Excellent leadership and mentoring for our entry-level to senior staff, and recognition of outstanding efforts - Team building events, team lunches/happy hours, and other company-wide events - A supportive, caring environment dedicated to continuous learning and growth

• Own the enterprise data governance framework within Tableau Cloud, including data source certification workflows, Tableau Catalog configuration (lineage tracking, data quality warnings, sensitivity labels), metric governance via Tableau Pulse, and enforcement of naming conventions, access controls, and content promotion policies. • Implement and manage row-level security, object-level security, and Virtual Connection-level entitlements to centralize and enforce data access controls. • Leverage the Platform Data API to build automated audit trails, activity monitoring pipelines, and compliance dashboards for ongoing governance observability. • Partner with BI to maintain a single source of truth for KPIs and metrics across the organization. • Lead the design and governance of the semantic data model to support Tableau Next AI features, including Tableau Pulse and Einstein Copilot. • Own Tableau Pulse metric definitions - defining, certifying, and deprecating official metrics organization-wide. • Guide governance and quality standards for AI-generated content to ensure outputs align with the organization’s trusted data standards. • Develop optimized semantic layers and certified data sources for Tableau dashboards and analytics. • Implement best practices for star schema design, LOD calculations, and data blending. • Diagnose and tune underperforming dashboards using Tableau Performance Recorder, database query analysis, and Admin Insights dashboards for site-wide performance monitoring. • Collaborate with other departments to integrate Tableau Cloud with upstream systems (e.g., Salesforce, Redshift).

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director, Data engineering Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realise their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview The CNPF Data & AI organisation is looking for a Director of Data Engineering to lead the strategy, architecture, and delivery of the data platform powering our analytics products and agentic AI applications across Small & Medium Enterprise (SME), Corporate Solution, Transfer Solution and Commercial Verticals. This is a senior, hands-on technical leadership role within Data & AI Product Enablement. The Director will own the data backbone that our LLM agents, MCP servers, and analytics products run on - making sure data is reliable, governed, retrievable in real time, and ready for AI consumption at production scale. The role works in close partnership with Applied AI, Product, and Architecture leadership. Role Own the data engineering strategy and technical direction for CNPF, with a strong focus on enabling agentic AI and GenAI products in production Architect and deliver the data foundations for multi-agent systems - including MCP servers exposing data and tools to agents, retrieval pipelines, vector stores, feature stores, and knowledge graphs Lead the design of context-engineering infrastructure that lets agents reason over Mastercard data safely, with the right grounding, freshness, and access controls Drive lakehouse, streaming, and event-driven platform design (Databricks, Spark, Kafka, Delta/Iceberg) to support both batch analytics and low-latency AI use cases Ensure data systems meet Mastercard standards for governance, lineage, data quality, observability, and risk - including the additional requirements that come with AI consumption (PII handling, prompt/response logging, audit trails) Set technical standards for how data products are exposed to agents and applications, including MCP design patterns, schema contracts, and tool interfaces Partner with Applied AI on evaluation and runtime data needs - training sets, eval datasets, retrieval quality, and feedback loops Stay hands-on enough to make sharp architectural calls, review designs, and unblock the team on hard problems Guide a team of senior data engineers, providing technical direction and growing their capability over time ALL ABOUT YOU Significant experience leading the design and delivery of large-scale data platforms in production Deep expertise in distributed data processing and the modern data stack - Spark, Databricks, Kafka, dbt, Delta/Iceberg, and similar Strong hands-on background in data architecture, modelling, streaming, and lakehouse design on AWS Proven track record of taking data systems from concept to secure, scalable production Solid grasp of data governance, lineage, quality, and observability frameworks Excellent technical communication - able to align engineers, AI scientists, product managers, and executives Comfortable operating as a player-coach: setting direction, reviewing designs, and going deep when needed What Makes You Stand Out You have personally built data infrastructure that powers agentic AI in production - not just analytics dashboards Hands-on experience designing and operating MCP (Model Context Protocol) servers, including authentication, tool exposure, schema design, and observability Direct experience building the data layer for multi-agent systems - retrieval, memory, state management, long-running workflow data, and human-in-the-loop checkpoints Strong familiarity with vector databases, hybrid retrieval (semantic + structured), and knowledge graph integration with LLMs Practical understanding of LLMOps data needs - eval datasets, golden traces, prompt/response telemetry, and feedback capture Experience designing real-time and event-driven systems that support low-latency agent decisioning Sharp instincts for the trade-offs between batch and streaming, structured and unstructured, accuracy and cost - and how those decisions cascade into agent behaviour Experience partnering with security and governance teams to ship AI-facing data products responsibly at enterprise scale Corporate Security Responsibility Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks come with inherent risk and therefore it is expected that the successful candidate will: Abide by Mastercard's security policies and practices Ensure the confidentiality and integrity of the information being accessed Report any suspected information security violation or breach Complete all mandatory security trainings in accordance with Mastercard's guidelines Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.