Data Solution Architect | Data Engineer & Cloud Analytics

Description

Can you imagine participating in the transformation of leading national and international organizations? At Deloitte, we are committed to generating impact for society, our clients, and you. About the position We are seeking a Data Solution Architect to strengthen our Data Engineering and Data Architecture team. This role emphasizes technical excellence, solution design, innovation, and leadership of other specialists. The selected candidate will serve as the technical reference point for data transformation and modernization projects. They will analyze our clients’ current data ecosystems, define target architectures, and develop roadmaps to evolve toward modern, scalable, secure, and governed data platforms. We seek a profile combining deep technological expertise, architectural vision, and consulting capability—able to collaborate effectively with both engineering teams and business and technology leaders. What will be your mission? Lead the definition of data architectures and solutions, ensuring their technical quality and alignment with client needs, while contributing to the development of capabilities within the Data Engineering, Data Architecture, and Cloud Data Platforms teams. **The position encompasses four dimensions:** Assessment and data modernization strategy. Architecture and technology selection. Technical leadership of solutions and teams. Development of standards, capabilities, and technical community. What responsibilities will you assume? Assessment and modernization strategy Lead technical and functional assessments of data ecosystems and platforms. Facilitate workshops with business, architecture, engineering, security, and governance teams. Analyze the as-is architecture, identifying risks, technical debt, gaps, and improvement opportunities. Define the to-be architecture and modernization roadmap, establishing initiatives, priorities, phases, and dependencies. Translate client objectives and use cases into architectural principles and decisions. Architecture design and technology selection Design modern data architectures in cloud, hybrid, and, when necessary, on-premise environments. Define Data Lake, Data Warehouse, and Lakehouse solutions—including integration patterns, batch and streaming processing, storage, and consumption. Incorporate requirements for security, governance, quality, observability, scalability, resilience, and cost efficiency. Evaluate cloud technologies, specialized platforms, and open-source components, justifying their suitability for the client’s context. Develop reference architectures, diagrams, standards, and design decisions. Lead proof-of-concepts or technical validations when needed to mitigate risk. Technical leadership and communication Act as the technical reference or design authority on complex projects. Guide data architects, data engineers, and other specialists during design and implementation. Conduct architecture reviews and ensure consistency between the defined solution and the final implementation. Resolve complex technical decisions and facilitate agreement across teams and disciplines. Communicate and defend recommendations to technical and executive stakeholders, tailoring the message to each audience. Participate as the solution reference in proposals, estimations, and technical defenses—without commercial or financial management being the primary focus of this role. Technical excellence and capability development Define and promote principles, patterns, best practices, and reusable assets. Mentor data architects, specialists, and data engineers. Drive technical reviews, design sessions, and knowledge sharing. Contribute to the evolution of Data Engineering and Data Architecture capabilities. Maintain an up-to-date market perspective and evaluate emerging technologies and approaches. Foster a culture of quality, continuous learning, and engineering excellence. What profile are we looking for? Professional experience More than 6 years of experience in data engineering, architecture, or data platforms. Proven experience designing and implementing enterprise-scale data solutions. At least 4 years of relevant experience with cloud platforms. Experience as a Data Architect, Cloud Architect, Solution Architect, or Technical Reference. Experience leading assessments, gap analyses, and defining as-is and to-be architectures. Experience developing modernization, migration, or technology transformation roadmaps. Ability to lead multidisciplinary teams technically and coordinate decisions across different areas. Experience communicating and defending architectures to technical and executive stakeholders. Prior experience in technology consulting and large organizations is valued. Education University degree in Computer Engineering, Telecommunications, Industrial Engineering, Mathematics, Physics, or another equivalent technical discipline. Languages Fluent English (B2/C1, preferably C1). You must be able to lead meetings, defend architectures, and author complex technical documentation in English. Ability to participate in proposals, meetings, and presentations in international contexts. Ability to lead meetings, facilitate workshops, defend architectures, and author technical documentation in English. Technological knowledge Expert-level mastery of all technologies is not expected; however, a solid foundation in cloud architecture, deep expertise in several core capabilities, and sound judgment for evaluating alternatives and justifying decisions are required. **Experience in the following areas is valued:** Cloud and data platforms Design of data solutions on AWS, Microsoft Azure, or Google Cloud Platform. Cloud architecture expertise in security, networking, observability, resilience, automation, and cost optimization. Platforms such as Databricks and Snowflake. Design of Data Lake, Data Warehouse, and Lakehouse architectures. Data engineering Distributed processing with Apache Spark. Orchestration using tools such as Airflow, Dagster, or Prefect. Transformation and Analytics Engineering practices with dbt. Streaming and event-processing architectures using Kafka or Flink. Storage formats and transactional tables such as Parquet, Delta Lake, Iceberg, or Hudi. Architecture, governance, and quality Data architecture patterns, including Lakehouse, Lambda, Kappa, event-driven architectures, and Data Mesh. Dimensional modeling, Data Vault, and consumption-oriented analytical models. Data governance, cataloging, metadata, lineage, and data quality. Design of secure, governed, and operationally ready scalable platforms. Automation and DataOps Infrastructure-as-code, preferably with Terraform. CI/CD, DevOps, and DataOps practices applied to data platforms and pipelines. Automation of testing, quality controls, deployments, and environment promotions. Valuable certifications **Certifications related to the following are valued:** AWS, Microsoft Azure, or Google Cloud Platform. Databricks. Snowflake. Cloud architecture. Certifications are considered a positive factor, though real-world experience in solution design, technical leadership, and architectural decision-making remains the top priority. Key competencies Technical excellence and judgment Deep technological expertise and ability to apply knowledge to complex business problems—avoiding solutions driven solely by a specific tool or vendor. Architectural thinking Holistic vision to jointly consider data, integration, infrastructure, security, governance, operations, and consumption. Solution orientation Ability to translate business needs into viable, scalable, efficient, and sustainable technical solutions. Technical leadership and influence Ability to guide other professionals, resolve complex decisions, establish standards, and build consensus without relying on direct hierarchical authority. Strategic communication Ability to engage in technical discussions with engineering teams as well as executive presentations for business and technology leaders. Client orientation Ability to understand the client’s context and formulate recommendations that balance value, feasibility, risk, and technological ambition. Collaboration and continuous learning Willingness to share knowledge, mentor peers, and stay current in a rapidly evolving technology landscape. Other requirements Ability to work with multidisciplinary and distributed teams. Flexibility to participate in projects across diverse sectors and technological contexts. Orientation toward quality, reusability, and knowledge creation. Technical contribution to proposals and solution defenses is valued. Financial management and commercial account development are not the primary focus of this role. What is it like to work at Deloitte? High-impact projects offering long-term growth and learning opportunities **️ A hybrid-flexible day-to-day:** flexible working hours and a healthy balance between remote work and in-person collaboration—in our offices or at client sites **A great atmosphere both inside and outside the