Senior Data Architect

The Role Provide overall technology leadership for the data transformation program, with accountability for data architecture, Data Mesh implementation, and the end-to-end delivery of data products. Work with client leadership, domain teams, architects, analysts, modelers, platform teams, and engineers to translate business priorities into scalable data products and reusable enterprise capabilities. Your responsibilities Define and govern the overall data architecture, Data Mesh implementation approach, and data product delivery principles for the program. - Act as the overall program technology lead, ensuring alignment across business priorities, domain architecture, data modelling, platform capabilities, engineering, governance, and consumption requirements. - Work with different levels of client management to support strategy definition, delivery planning, implementation oversight, architectural decision-making, and frictionless delivery of data products. - Collaborate with domain consultants and business stakeholders to identify, define, decompose, and prioritize data products. - Establish architecture standards and decision frameworks for data product boundaries, domain ownership, interoperability, sharing, discoverability, quality, security, and lifecycle management. - Lead the design of reusable frameworks, foundational capabilities, templates, and components that accelerate the end-to-end data product lifecycle. - Lead proofs of concept, proofs of technology, architecture assessments, and evaluation exercises, and present findings and recommendations to client stakeholders. - Work with engineering teams to ensure optimal data product design, including ingestion, transformation, storage, orchestration, quality, security, observability, and consumption patterns. - Review solution designs, resolve cross-domain architecture concerns, manage technical dependencies, and govern architecture exceptions. - Ensure alignment between data product delivery and enterprise data governance, metadata, lineage, access control, data quality, and certification requirements. - Provide technical direction to architects, data modelers, analysts, and engineers, and facilitate architecture and design reviews across delivery teams. - Identify architectural risks and delivery constraints, define mitigation actions, and communicate technology decisions and implications to program leadership. - Drive consistency and reuse across domains while allowing appropriate autonomy for domain-specific implementation decisions. Essential skills/knowledge/experience: Strong experience leading enterprise data architecture and large-scale data transformation programs. - Deep understanding of Data Mesh, data products, domain-driven design, federated governance, data product lifecycle management, and data-as-a-product principles. - Experience defining enterprise, domain, conceptual, logical, and physical data architectures. - Strong understanding of end-to-end data lifecycle management. - Experience designing reusable data platform capabilities, engineering frameworks, architecture patterns, and delivery accelerators. - Ability to translate business strategy and domain requirements into pragmatic architecture and executable delivery plans. - Experience leading proofs of concept, technology evaluations, architecture reviews, and executive-level presentations. - Strong understanding of modern data platforms like databricks - Proven ability to lead multidisciplinary teams involving domain experts, business analysts, data modelers, platform architects, governance specialists, and data engineers. - Strong stakeholder management, facilitation, technical leadership, communication, and decision-making skills. Preferred Qualifications ------------- - Experience implementing Data Mesh or domain-oriented data product operating models in a large enterprise. - Experience working in regulated industries. - Knowledge of Databricks, cloud data platforms (AWS), semantic layers, data catalogues, and modern data governance solutions. - Experience establishing architecture governance, design authorities, reusable knowledge assets, and data product standards. - Relevant AWS Cloud, data architecture, enterprise architecture, or Databricks certification.Nice to Have • Databricks Certified Data Engineer Associate/Professional. • Experience working with globally distributed teams and enterprise-scale data platforms. • Exposure to AI/ML workloads on Databricks. Desirable skills/knowledge/experience: · Experience in Commodity Trading, Energy Trading, or Supply Chain domains. · Exposure to real-time data processing and event-driven architectures. · Knowledge of Power BI, Tableau, or other analytical reporting platforms. · Understanding of Data Mesh architecture and data product thinking. · Databricks certification is preferred. Primary Technologies: Databricks, PySpark, Delta Lake, Unity Catalog, Delta Live Tables, SQL, Azure , Git, CI/CD, Data Modeling.