Data Solutions Architect | Data Engineer & Cloud Analytics

What profile are we looking for?

Professional experience

• More than 6 years of experience in engineering, architecture, or data platforms.
• Proven experience designing and implementing enterprise-scale data solutions.
• At least 4 years of relevant experience in cloud platforms.
• Experience as a data architect, cloud architect, solution architect, or technical reference.
• Experience leading assessments, gap analyses, and definition of as-is and to-be architectures.
• Experience developing modernization, migration, or technological transformation roadmaps.
• Ability to technically lead multidisciplinary teams and coordinate decisions between different areas.
• Experience communicating and defending architectures to technical and executive interlocutors.

• Previous experience in technology consulting and large organizations will be valued.

Technological knowledge

Expertise in all technologies is not expected, but a solid foundation in cloud architecture, depth in several of the main capabilities, and criteria to evaluate alternatives and justify decisions is required.

Experience in the following will be valued:

Cloud and data platforms

• Designing data solutions on AWS, Microsoft Azure, or Google Cloud Platform.
• Cloud architectures in terms of security, networks, observability, resilience, automation, and cost optimization.
• Platforms such as Databricks and Snowflake.
• Designing Data Lake, Data Warehouse, and Lakehouse architectures.

Data engineering

• Distributed processing with Apache Spark.
• Orchestration with tools such as Airflow, Dagster, or Prefect.
• Transformation and Analytics Engineering practices with dbt.
• Streaming and event processing architectures with technologies such as 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 models oriented to analytical consumption.
• Governance, catalog, metadata, lineage, and data quality.
• Design of secure, governed, and operation-ready platforms at scale.

Automation and DataOps

• Infrastructure as code, preferably with Terraform.
• CI/CD, DevOps, and DataOps practices applied to platforms and data pipelines.
• Automation of tests, quality controls, deployments, and promotions between environments.

Education

University degree in Computer Engineering, Telecommunications, Industrial Engineering, Mathematics, Physics, or another equivalent technical discipline.

Valuable certifications

Certifications related to:

• AWS, Microsoft Azure, or Google Cloud Platform.
• Databricks.
• Snowflake.
• Cloud architecture.

Certifications will be a positive element, although real experience in solution design, technical leadership, and architectural decision-making will be prioritized.

• Fluent English (B2/C1, preferably C1). You must be able to lead meetings, defend an architecture, and write complex technical documentation in English.
• Ability to participate in proposals, meetings, and presentations in international environments.
• Ability to lead meetings, facilitate workshops, defend architectures, and write technical documentation in English.

What is it like to work at Deloitte?

🤩 High-impact projects where you will have a long career and learning path

☯️ Hybrid-flexible day-to-day: you will have flexible hours and a good balance between remote work and teamwork in our offices or those of our clients

⚽ Good atmosphere inside and outside the office: you will enjoy several team-building activities per year, cultural and sports activities... and much more!

🧘♀️ Comprehensive well-being: take care of yourself with our physical, mental, and financial health program... and with a medical team in the offices!

🤲 Social impact: You can sign up for a large number of national and international volunteering opportunities and pro-bono projects to put your time and talent at the service of those who need it most

🗣️Feedback and continuous learning culture: you will grow in an inclusive environment where equal opportunities and your personalized training plan will boost your development. Can you already see yourself at the Deloitte University in Paris?

🤝 Exclusive benefits for being part of Deloitte: you will be able to enjoy a wide catalog of benefits and a comprehensive flexible compensation plan

About the position

We are looking to hire a data solutions architect to strengthen our Data Engineering and Architecture team.

The position focuses on technical excellence, solution design, innovation, and leading other specialists. The selected person will act as a technical reference in data transformation and modernization projects. They will analyze the current ecosystems of our clients, define target architectures, and develop roadmaps to evolve towards modern, scalable, secure, and governed data platforms.

We are looking for a profile that combines technological depth, architectural vision, and consulting capacity, able to work with both engineering teams and business and technology managers.

What will your mission be?

Lead the definition of data architectures and solutions, ensuring their technical quality and alignment with the client's needs, and contribute to the development of the capabilities of the Data Engineering, Data Architecture, and Cloud Data Platforms team.

The position combines four dimensions:

• Data modernization assessment and strategy.
• Architecture design and technology selection.
• Technical leadership of solutions and teams.
• Development of standards, capabilities, and technical community.

What responsibilities will you assume?

Data modernization assessment

• 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 the client's 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 security, governance, quality, observability, scalability, resilience, and cost-efficiency requirements.
• Evaluate cloud technologies, specialized platforms, and open-source components, justifying their suitability to the client's context.
• Develop reference architectures, diagrams, standards, and design decisions.
• Lead proof of concepts or technical validations when necessary to reduce risks.

Technical leadership and communication

• Act as a technical reference or design authority in complex projects.
• Guide architects, data engineers, and other specialists during design and implementation.
• Perform architecture reviews and ensure consistency between the defined and finally built solution.
• Resolve complex technical decisions and facilitate agreements between teams and disciplines.
• Communicate and defend recommendations to technical and executive stakeholders, adapting the message to each audience.
• Participate as a solution reference in proposals, estimates, and technical defenses, without commercial or financial management being the main focus of the position.

Technical excellence and capability development

• Define and promote principles, patterns, best practices, and reusable assets.
• Mentor architects, specialists, and data engineers.
• Drive technical reviews, design sessions, and knowledge exchange.
• Contribute to the evolution of Data Engineering and Data Architecture capabilities.
• Maintain an updated vision of the market and evaluate new technologies and approaches.
• Promote a culture of quality, continuous learning, and engineering excellence.

Technical excellence and criteria

Technological depth and ability to apply knowledge to complex business problems, avoiding solutions conditioned exclusively by a tool or manufacturer.

Architectural thinking

Integral vision to consider data, integration, infrastructure, security, governance, operation, and consumption together.

Solution orientation

Ability to translate a business need into a viable, scalable, efficient, and sustainable technical solution.

Technical leadership and influence

Ability to guide other professionals, resolve complex decisions, establish standards, and generate consensus without depending on direct hierarchical authority.

Strategic communication

Ability to handle both technical conversations with engineering teams and executive presentations to business and technology managers.

Customer orientation

Ability to understand the client's context and formulate recommendations that balance value, viability, risk, and technological ambition.

Collaboration and continuous learning

Willingness to share knowledge, mentor other professionals, and stay updated in a constantly evolving technological environment.

Other requirements

• Ability to work with multidisciplinary and distributed teams.
• Flexibility to participate in projects from different sectors and technological contexts.
• Orientation to quality, reuse, and knowledge generation.
• Technical contribution to proposals and solution defenses will be valued.
• Financial management and account development are not the main focus of the position.