Description
Can you imagine participating in the transformation of leading national and international organizations?
At Deloitte, we are committed to generating impact on society, our clients, and you.
About the position
We are seeking to hire a Technology Consulting Manager or Senior Manager to strengthen our Data Engineering and Data Architecture team.
The selected candidate will play a key role in the practice’s growth, combining business development, client leadership, solution design, and end-to-end project delivery for Data & Analytics initiatives. We seek a profile with commercial autonomy, ability to manage complex initiatives, and experience leading consulting teams in demanding technology environments.
You will be responsible for driving data-centric opportunities, building trusted relationships with clients and technology partners, and ensuring the technical, financial, and operational success of projects under your responsibility.
What will be your mission?
Contribute to the development of our Data Engineering, Data Architecture, and Cloud Analytics offerings—leading both commercial activities and project execution, as well as team evolution.
**The role combines four core dimensions:**
Business development and management of large accounts.
Technical and financial project leadership.
Support in defining data architectures and solutions.
Team leadership, development, and growth.
What responsibilities will you assume?
Business development and commercial leadership
Identify, develop, and lead commercial opportunities related to Data Engineering, Cloud Analytics, Data Platforms, and Data Strategy.
Manage client relationships, generate new opportunities, and contribute to account opening and expansion.
Lead complex, large-scale pre-sales processes and responses to RFPs.
Coordinate proposal development, financial estimations, service delivery models, and work plans.
Deliver commercial and technical presentations to business and technology stakeholders.
**Define value propositions and solutions around:**
Data Strategy and Data Assessments.
Modern Data Platforms and Data Lakes.
Cloud, hybrid, and on-premise data architectures.
Business Intelligence and Analytics.
DataOps and MLOps.
Streaming platforms and real-time processing.
Develop relationships with alliances and technology partners, identifying joint market opportunities.
Project leadership and financial management
Concurrently lead a portfolio of approximately three to four projects.
Ensure delivery against scope, quality, timeline, and budget commitments.
Manage risks, dependencies, planning, capacity, and team workload.
Monitor project financial performance—including revenue, costs, margin, forecasts, and variances.
Maintain executive-level client engagement throughout the project lifecycle.
Participate in resolving critical situations by facilitating decision-making and defining action plans.
Ensure deliverable quality and solution alignment with client objectives.
Technical and solution leadership
Lead the definition of data architectures and solutions from a management, feasibility, value, and commercial positioning perspective.
Guide teams in selecting technologies, architectural patterns, and implementation models.
Bridge business needs with scalable, secure, and sustainable data engineering and architecture solutions.
Participate in architecture reviews, estimations, transition plans, and technology roadmaps.
Identify technical and operational risks during pre-sales and execution phases.
Team management and development
Lead teams of 10–20 professionals, with potential to scale to structures exceeding 20–25 people as the practice grows.
Coordinate managers, architects, specialists, consultants, and engineering profiles.
Build cohesive teams and develop capabilities—supporting recruitment, training, and professional growth.
Monitor team performance, professional development, assignment, and utilization.
Promote collaboration, autonomy, and knowledge sharing.
Serve as a role model for the team—establishing methodology, best practices, and a culture of technical excellence and client orientation.
What profile are we looking for?
Professional experience
Minimum two years’ prior experience as a Manager on Data, Analytics, Cloud, or technology transformation projects.
Proven experience in technical and financial leadership of consulting projects.
Experience managing multiple projects simultaneously—with accountability for timelines, risks, budget, margin, and teams.
Experience developing and managing large accounts.
Experience leading pre-sales efforts, proposals, and RFP responses.
Ability to define and defend data architectures and solutions before technical and executive stakeholders.
Experience managing teams of more than 10 people.
Experience managing a unit, project portfolio, or account with financial performance accountability is highly valued.
Education
**University degree in:**
Computer Engineering.
Telecommunications Engineering.
Industrial Engineering.
Mathematics.
Physics.
Other equivalent technical degrees.
Languages
Fluent English (B2/C1; C1 preferred). You must be able to lead meetings, defend architectures, and author complex technical documentation in English.
Ability to participate in proposals, meetings, and presentations within international contexts.
Technical knowledge
We seek a profile with broad vision of data architectures and the ability to make decisions and lead solutions. Hands-on technical specialization across all technologies is not required; however, sufficient knowledge is expected to guide proposals, validate architectures, and hold high-level discussions with clients and technical teams.
**Experience in the following areas will be valued:**
Data architectures and platforms
Analytics architectures in cloud, hybrid, and on-premise environments.
Data Lakes, Data Warehouses, Lakehouse, and Modern Data Platforms.
Batch, streaming, and event-driven processing architectures.
Data integration, governance, security, and quality.
DataOps, DevOps, and MLOps applied to data platforms.
Cloud and analytics platforms
**Microsoft Azure:** Azure Data Factory, Azure Data Lake, Synapse Analytics, Azure SQL, Analysis Services, Databricks, Delta Lake, and Power BI.
**Google Cloud Platform:** Cloud Storage, Dataproc, Dataflow, BigQuery, and Google Cloud ecosystem visualization tools.
**Amazon Web Services:** AWS Lambda, Glue, S3, Redshift, Athena, Redshift Spectrum, and Kinesis.
Snowflake.
Databricks.
Data engineering and integration
Apache Kafka, Kafka Connect, and event-processing technologies.
Hadoop ecosystems and platforms such as Cloudera.
SQL databases—including Oracle, Microsoft SQL Server, and MySQL.
Data integration, transformation, and exploitation tools and patterns.
Valuable certifications
**Professional certifications related to:**
Microsoft Azure.
Google Cloud Platform.
Amazon Web Services.
Snowflake.
Databricks.
Service and project management—e.g., ITIL or PMP.
Certifications will be considered a positive factor, although real-world experience in client management, commercial development, team leadership, and project direction will take priority.
Key competencies
Client orientation
Ability to understand client priorities, build trusted relationships, and translate business needs into concrete initiatives and solutions.
Communication and influence
Executive-level communication—clear, concise, and persuasive. Ability to present and defend proposals before business leaders, CIOs, CDOs, architecture leads, and technical teams.
Commercial autonomy
Ability to build client relationships, uncover opportunities, mobilize internal teams, and lead commercial defenses with minimal external dependency.
Commercial capability
Experience leading complex RFPs, articulating value propositions, designing solutions, and coordinating the technical, financial, and operational components of an offer.
Leadership
Ability to lead multidisciplinary teams, delegate responsibilities, develop talent, and support practice growth.
Teamwork
Orientation toward building sustainable capability, sharing knowledge, and fostering a community of professionals focused on data engineering and architecture.
Financial management
Solidity in budgeting, forecasting, margin analysis, resource allocation, and capacity planning.
Initiative and proactivity
Ability to anticipate needs, identify opportunities, and make decisions in complex or information-scarce contexts.
Technology and business vision
Ability to evaluate a solution not only by its technical suitability but also by its economic viability, scalability, impact, and alignment with the organization’s strategy