Data Architect

Role 1 -Data Architect Role Summary The Information Architect is the end-to-end technical authority for the HR Analytics data estate, owning architecture from upstream authoritative source systems through to certified data products delivered in Microsoft Fabric. This role defines integration contracts with source-system owners, owns the conceptual, logical, and physical data models, aligns the enterprise business glossary, and establishes the engineering quality standards for all pipelines and data products. This is a hands-on technical leadership role. The Information Architect designs systems, leads architecture and design reviews, contributes directly to complex pipeline implementation, and resolves the most challenging engineering problems across the platform. The role is delivery-adjacent, fast-paced, and directly shapes the quality of data products consumed by HR business stakeholders. Scope of Responsibility End-to-End Information Architecture Ownership The Information Architect owns the full HR Analytics architecture across: Upstream (Source Systems) Own integration contracts with authoritative source systems including Workday, ServiceNow, internal HR platforms, and other systems of record. Own the canonical data model and integration contract; source-system teams retain ownership of their internal implementations. Midstream (Data Platform & Lakehouse) Define ingestion patterns and medallion architecture (bronze, silver, gold). Own transformation logic, Databricks lakehouse design, Unity Catalog governance, and Azure data platform standards. Downstream (Consumption & Analytics) Own semantic layer design and certified data product delivery in Microsoft Fabric. Define Fabric IQ patterns, OneLake organization, and consumption-ready models for Power BI and AI/ML workloads. How the Team Works The HR Analytics engineering team operates as one global team across the US and India. The team is structured into three layers: Information Architect – owns end-to-end architecture and engineering standards. Principal Data Engineers – set the engineering bar and lead delivery. Senior, Data, and Associate Data Engineers – deliver data products end-to-end. Engineers are distributed across Frisco, TX; PST US locations; and Hyderabad, India, partnering across time zones to maintain ownership and delivery momentum. Business engagement is led through senior engineering and architecture leadership, with broader team participation growing as engineers gain domain expertise. Work flows from business need → technical design → ingestion, unified framework, data modeling, transformation across Databricks and Snowflake, semantic layer in Microsoft Fabric, and visualization in Power BI. The team operates a DevOps ownership model, including shared on-call rotation and production support. Core Responsibilities Own the end-to-end information architecture for HR Analytics, from authoritative source systems through ingestion, transformation, lakehouse, semantic layer, and certified Fabric data products. Own and maintain conceptual, logical, and physical data models for HR Analytics, aligned to the enterprise business glossary and HR domain semantics across: Talent Workforce Compensation Learning People Analytics Define and own integration contracts with upstream source-system teams, including: Data delivery patterns (batch, CDC, streaming) Schema agreements SLA commitments Change management protocols Establish and enforce engineering standards for data modeling, pipeline design, testing, documentation, and reliability. Lead architecture and design reviews, setting the quality bar for all HR Analytics data products. Act as a hands-on technical leader, contributing directly to complex pipeline builds and resolving critical engineering challenges. Partner closely with Principal Data Engineers to guide platform evolution and implementation patterns. Role 2 -Data Architect - Revenue Data Platform We are looking for someone who can architect a scalable revenue data platform to support enterprise-wide data needs and deliver actionable insights across Client business units. Our current tech stack includes Azure, Snowflake, Databricks, Claude, and GitLab, with AWS also available. Furthermore, having knowledge of finance domain and platforms like SAP and Oracle is an added advantage. The ideal candidate will bring a forward-thinking approach—able to translate vision into architecture and design, develop proof of concepts, incorporate cost considerations, and deliver incremental value aligned to specific business units. This is a critical role that requires strong ownership, a bias for action, and the ability to balance strategic thinking with hands-on collaboration at the engineering level. Role Overview We are seeking a highly skilled Data Architect to lead the design and evolution of our Revenue Data Platform (RDMP). This role will be instrumental in architecting a scalable, enterprise-grade data platform that enables unified data access and delivers actionable insights across Client business units. The ideal candidate will bring a forward-looking mindset, translating strategic vision into practical architecture, while driving innovation, cost efficiency, and measurable business outcomes. Key Responsibilities Define and architect a scalable, enterprise-wide Revenue Data Platform to support diverse business needs Translate business vision into robust data architecture, design patterns, and implementation roadmap Develop proof of concepts (POCs) to validate architectural decisions and accelerate adoption Design solutions leveraging modern data platforms including Azure, Snowflake, Databricks, and AWS Collaborate closely with engineering teams to ensure hands-on alignment and execution Incorporate cost optimization strategies into architecture and platform design Deliver incremental value aligned to specific business units through phased implementation Ensure data solutions enable high-quality, secure, and governed data access across the enterprise Required Qualifications Proven experience as a Data Architect designing and implementing large-scale data platforms Strong expertise in cloud data ecosystems (Azure preferred; AWS experience is a plus) Hands-on experience with Snowflake, Databricks, and modern data engineering practices Experience working with CI/CD tools such as GitLab Ability to bridge strategic architecture and hands-on engineering execution Strong understanding of data modeling, data governance, and data platform scalability Preferred Qualifications Experience in Finance/Revenue domains Familiarity with enterprise platforms such as SAP and Oracle Exposure to AI/LLM tools (e.g., Claude) and their integration into data platforms