Project management
Planning, prioritisation and task tracking, stakeholder coordination, risk management and adaptation to change with a practical approach, using Agile when it makes sense.
Data Engineering · Cloud · Delivery
Rosalía Contreras Moreira
Data & Cloud Engineer with experience in technical project coordination and delivery.
I act as a bridge between business and technical teams on data and cloud projects.
About me
I am a Data & Cloud Engineer with experience in data environments and cloud platforms (GCP/Azure). Throughout my career I have worked on technical projects collaborating closely with engineering and business teams, participating in planning and task tracking from a primarily technical role.
I'm good at explaining technical matters to decision-makers and bringing order to projects.
In addition to my technical profile, I design and develop landing pages and simple websites for small businesses, focused on clarity, structure and lead generation.
- Hybrid profile: Data Engineering and technical project work with a holistic vision.
- Experience in automation, pipelines and cloud architectures.
- People-oriented, with a focus on communication and clarity in daily work.
- Design and development of landing pages and simple websites for small businesses.
What I do
I bring a mix of project vision and technical foundation so that technology decisions make sense for the business and are sustainable for the teams.
Data and cloud
Prior experience in data engineering and cloud environments (GCP/Azure), pipelines, automation and technical best practices that help ensure projects move beyond the idea stage.
Business ↔ technology bridge
I help teams and clients understand what is being built, why, and how it impacts results, making sure the technical conversation is understandable and useful.
Projects
Projects and use cases
Examples where technical work meets a Project Management approach.
AI and meeting management
Automation of daily stand-up summaries with generative AI
Design of a workflow to convert daily stand-up notes into clear summaries: blockers, next steps and owners. Format standardisation and partial automation.
Role: process definition, prompts, output structure and pilot test with the team.
Cloud adoption
Cloud tool adoption support for a technical team
Support during the transition to cloud solutions (GCP/Azure), documenting processes and creating guides so the team could work consistently.
Role: liaison between business, technical team and best practice documentation.
Risk management
Academic project: Risk management in data projects
Identification of technical and planning risks (dependencies, technical debt, deadlines, data quality) and proposal of mitigation measures.
Role: analysis, risk prioritisation and design of mitigation actions.
Experience
Transitioning from data engineering towards a technical Project Management role, combining hands-on experience in data and cloud with a master's in project management.
Consultant · Process Diagnosis and Transformation
Diagnosis and improvement of internal operations at a family-owned construction materials distribution company. The work starts from direct observation and interviews with the team.
- Organisational diagnosis across 4 operational areas: store, warehouse, logistics and call centre
- Identification of communication gaps and critical cross-department dependencies
- Analysis of how information flows and where tacit knowledge concentrates
- Design of prioritised improvement proposals and presentation to management
Data & Cloud Engineer · transitioning to Project Manager
Technical role within data and cloud projects, combining day-to-day work with intensive Project Management training. Involvement in the analysis, design and maintenance of data-driven solutions and coordination with other profiles.
- Design and maintenance of data pipelines in cloud environments.
- Collaboration with multidisciplinary teams (business, development and infrastructure).
- Documentation and communication of technical progress and decisions.
- Participation in internal process improvement and automation initiatives.
Data Engineer
Strategic consultancy in capital markets · End-to-end management of data pipelines on GCP.
- GCP specialisation: design, maintenance and scaling of pipelines.
- BigQuery: maintenance of centralised multi-department data flows.
- Dataform & Dataproc: building scalable ETL processes.
- Data integration from Funnel into the GCP ecosystem.
- Structured and unstructured data ingestion management.
- Tools: BigQuery, Dataform, Dataproc, Python, StreamSet, Git, Spark, n8n.
Data Engineer
Innovation and technology consultancy, involvement in cloud projects and predictive models.
- Enel: pipeline development in Data Lake/DWH for batch and streaming.
- API design and ingestion processes for heterogeneous datasets.
- Air Nostrum: support for predictive model, weather scraping and data extraction.
- Tools: Python (Streamlit, Pandas, Matplotlib), SQL, MongoDB, APIs, Azure, Git, Airflow.
Data Engineer
Strategic consultancy in innovation and technology · Projects focused on trends and DataOps.
- Horizon 2020: creation and cleansing of SQL database.
- Scraping and MongoDB for technology trend analysis.
- API integrations and pipelines for EPO, WIPO and Crunchbase.
- Tools: Python, Selenium, BeautifulSoup, PostgreSQL, MongoDB, APIs, Azure, Git.
Data Engineer · Data Analyst · IT Developer
Full career path across data, analysis, reporting, internal development and regulatory compliance.
- Data Engineer (2017-2019): reporting, data analysis, daily processes with Morningstar/Bloomberg.
- Data Analyst (2012-2017): support for investment strategies and institutional clients.
- IT Developer (2002-2012): intranet, web, advanced SQL, Solvency I/II/III.
- Tools: SQL Server, VBA, Excel, Python, Reuters, Bloomberg, HTML, ASP, JS, XML.
Education
Education and certifications
Master's in Project Management
IEBS Business School
Completed · Oct. 2026
Specialised Master's in Digital Project Management with a focus on agile methodologies and management of digital transformation projects. Practical training in leading technical teams and strategic planning.
Areas of specialisation:
- Agile methodologies: Scrum, Kanban, SAFe (Scaled Agile Framework), OKRs and Lean Change Management for distributed teams.
- Leadership and change management: Leading multidisciplinary teams, stakeholder communication and organisational change management.
- Financial management: Lean-Agile budgeting, ROI analysis, cost management and value metrics for digital projects.
- Product management: Product roadmaps, prioritisation using techniques such as MoSCoW, user stories, and collaboration with Product Owners.
- Risk management: Identification, assessment and mitigation plans for risks in technical and infrastructure projects.
- Technical environments: Coordination with DevOps teams, CI/CD pipeline management, cloud projects (AWS/Azure/GCP) and AI/ML solutions.
- PM tools: Jira, Confluence, Azure DevOps, MS Project, Trello, Asana and management reporting techniques.
💼 Practical projects completed: The master's included a monthly practical project applied to real cases: OKRs to align teams, a digital product prototype with value proposition validation, an OKR rollout in a training company moving into consultancy, and a time management app with a functional prototype in Figma (flows, interface and UX validation with AI).
Master's in Business Analytics & Big Data
IE Business School
Completed
Programme focused on the practical application of advanced analytics and Big Data technologies to drive decision-making and digital transformation.
- Advanced data analysis and machine learning.
- Big Data architectures: Hadoop, Spark, NoSQL, data warehousing and stream processing.
- SQL modelling and Python programming for analysis and prediction.
- Data visualisation and business-oriented storytelling.
- Data governance, privacy and applied ethics.
- Practical challenges: IBM Watson Challenge, Datathon and Big Data Startup.
Cloud certifications
Microsoft Azure
Completed
Azure fundamentals certifications aimed at understanding the foundation of cloud services and their impact on projects.
- AZ-900 · Azure Fundamentals.
- DP-900 · Azure Data Fundamentals.
Skills
Key competencies
Project management
- •Project planning and tracking.
- •Agile methodologies (Scrum and Kanban, learning and practice).
- •Stakeholder management and expectation alignment.
- •Status documentation and reporting.
- •Risk and dependency management.
Technology and cloud
- •Data Engineering (pipelines, ETL/ELT).
- •Google Cloud Platform & Microsoft Azure.
- •Relational and non-relational databases.
- •Python for automation and data.
Soft skills
- •Clear communication with diverse profiles.
- •Teamwork and collaboration.
- •Adaptability and continuous learning.