Principal Data Architect

Designation: Principal Data Architect About Us TheMathCompany or MathCo® is a global Enterprise AI and Analytics company trusted by leading Fortune 500 and Global 2000 enterprises for data-driven decision making. Founded in 2016, MathCo builds custom AI and advanced analytics solutions to solve enterprise challenges through its hybrid model. NucliOS, MathCo’s proprietary platform, enables connected intelligence at a lower total cost of ownership (TCO). At MathCo, we foster an open, transparent, and collaborative culture, making it a great place to work. We provide exciting growth opportunities and value capabilities and attitude over experience, enabling our Mathemagicians to "Leave a Mark." Job Description We are seeking a Principal Data Architect with 15+ years of experience in architecting, governing, and transforming enterprise-wide data ecosystems. This strategic leadership role requires deep expertise in defining enterprise data architecture roadmaps, modernizing data platforms, driving cloud transformation initiatives, and enabling AI-ready data foundations at scale. The ideal candidate will serve as a trusted advisor to business and technology leadership teams, shaping long-term data strategy and ensuring alignment between data, analytics, AI, and enterprise objectives. You will lead the design of scalable, secure, and future-ready architectures spanning data lakes, lakehouses, warehouses, streaming systems, and multi-cloud environments across AWS, Azure, and GCP. The role demands strong experience in enterprise data governance, data modernization, platform optimization, advanced metadata management, and large scale digital transformation programs. You will mentor senior architects and engineering teams while driving innovation through emerging technologies in AI, GenAI, Data Mesh, and modern data platforms. Key Responsibilities • Define and govern enterprise-wide data architecture strategy aligned with organizational goals and digital transformation initiatives. • Lead the design of scalable, cloud-native data platforms supporting analytics, AI/ML, GenAI, real-time processing, and operational workloads. • Establish architecture standards, reference frameworks, and best practices for data engineering, integration, governance, and security. Internal Use Only • Drive enterprise data modernization initiatives involving migration from legacy systems to modern cloud data ecosystems. • Provide architectural leadership for large-scale data lakes, lakehouses, data warehouses, and distributed data platforms. • Partner with business stakeholders, executive leadership, product teams, and technology leaders to translate business vision into strategic data capabilities. • Define enterprise data models, data domain strategies, metadata management frameworks, and master data management approaches. • Lead adoption of modern architectural patterns including Data Mesh, Data Fabric, Event-Driven Architecture, and Domain-Oriented Data Ownership. • Govern enterprise-wide data quality, lineage, cataloging, privacy, compliance, and access management frameworks. • Design highly available, fault-tolerant, and cost-efficient architectures across AWS, Azure, and GCP ecosystems. • Drive technology evaluation, vendor selection, and architectural decisions for platforms such as Databricks, Snowflake, Synapse, BigQuery, Redshift, and Fabric. • Oversee design and optimization of real-time streaming architectures using Kafka, Spark Streaming, Event Hubs, Kinesis, and similar technologies. • Collaborate with cybersecurity and governance teams to ensure compliance with global regulatory standards including GDPR, CCPA, HIPAA, and industry specific requirements. • Champion AI-ready data capabilities including feature stores, semantic layers, vector databases, knowledge graphs, and GenAI data architectures. • Mentor Data Architects, Principal Engineers, and senior technical leaders, fostering architectural excellence across the organization. • Establish framework for architecture reviews, solution governance, technology guidelines, and enterprise design decisions. • Drive platform optimization initiatives focused on scalability, resiliency, performance, and total cost of ownership. Required Skills and Experience Experience Internal Use Only • 15+ years of experience in Data Architecture, Data Engineering, Data Platform Engineering, or Enterprise Architecture. • 8+ years of experience designing and implementing enterprise-scale cloud based data solutions. • Proven track record of leading large-scale data transformation and modernization programs for global enterprises. • Experience working directly with executive stakeholders and driving strategic technology initiatives. Technical Expertise • Deep expertise in enterprise data architecture, information architecture, and data platform strategy. • Strong experience in designing and governing enterprise-wide data models across transactional, analytical, and operational systems. • Extensive experience building modern data platforms using AWS, Azure, and GCP services. • Expertise in large-scale distributed computing frameworks including Spark, Hadoop ecosystem, Databricks, and Snowflake. • Strong understanding of lakehouse architectures and modern cloud-native data ecosystems. • Experience with enterprise integration platforms and ETL/ELT frameworks such as Azure Data Factory, Informatica, Talend, Data Fusion, and Glue. • Expertise in relational, NoSQL, graph, vector, and time-series database technologies. • Strong proficiency in SQL, Python, Scala, Java, and distributed processing frameworks. • Experience architecting real-time streaming systems leveraging Kafka, Event Hub, Kinesis, Pub/Sub, and Spark Streaming. • Knowledge of MLOps, DataOps, CI/CD, Infrastructure as Code, and platform engineering principles. • Experience designing AI and GenAI-ready data architectures supporting advanced analytics and machine learning workloads. • Expertise in enterprise metadata management, data catalog solutions, and lineage frameworks. Internal Use Only Governance & Security • Strong understanding of enterprise data governance, stewardship, and operating models. • Experience implementing governance platforms supporting data quality, cataloging, lineage, and policy enforcement. • Expertise in designing secure data platforms with robust identity, access management, encryption, and auditing controls. • Strong knowledge of regulatory compliance requirements including GDPR, HIPAA, CCPA, and industry-specific data regulations. Leadership • Demonstrated ability to lead and influence cross-functional teams across architecture, engineering, product, and business functions. • Strong consulting, stakeholder management, and executive communication skills. • Proven experience mentoring senior technical professionals and driving architecture maturity across organizations. • Ability to align long-term technology vision with measurable business outcomes. Being a Mathemagician • Embody MathCo's culture and way of working. • Lead with ownership, accountability, and a strategic mindset. • Drive innovation and continuously challenge the status quo. • Act as a thought leader within the organization and the broader data community. • Foster collaboration, mentorship, and knowledge sharing across teams. • Support diversity and appreciate different perspectives. • Enable business growth through technology leadership and data-driven decision-making. Recognitions • Positioned as a Leader in Top Generative AI Service Providers – PeMa Quadrant 2023 by AIMResearch. Internal Use Only • Recognized among Inspiring Workplaces in North America, 2023. • Accredited for Inclusive Practices by Great Place to Work Institute, India. • Recognized among India's Best Workplaces™ for Diversity, Equity, Inclusion & Belonging 2023 by Great Place To Work® India. Internal Use Only