Daniel Chaves
Results-driven Delivery Manager with 6 years of experience leading enterprise data initiatives and cross-functional teams. Specializing in AI/ML solutions, modern data stack implementations, and data platform architecture.
Experience
Delivery Manager
•Indicium
Aug 2024 - Present•Remote
Lead data projects and analytics teams to deliver client-focused solutions.
Key Achievements
- Lead migrations of legacy data products to modern infrastructures and spearhead development of new solutions including data models, dashboards, and AI products using dbt, Dagster, Airflow, Snowflake and Databricks with robust data governance frameworks.
- Manage cross-functional teams of 30+ professionals, including data engineers, data analysts and analytics engineers, ensuring seamless collaboration and stakeholder alignment across multiple concurrent initiatives.
- Orchestrate over 10 projects simultaneously while overseeing 3000+ service hours monthly, optimizing resource allocation and maintaining consistent delivery timelines through strategic leadership.
- Engineer and deploy AI products from scratch - intelligent agents, machine learning models, generative AI solutions, and chatbots - expanding service offerings and driving increased client engagement.
- Lead stakeholder management efforts in expanding contracts with major pharmaceutical companies like Novo Nordisk and Bayer, driving significant revenue growth and strengthening client partnerships.
- Streamline project workflows by implementing agile practices, enhancing efficiency across multiple data and analytics streams.
- Drive strategic planning for tailored data strategies to address business needs, with a strong focus on enterprise-level clients in the pharmaceutical sector.
- Cultivate professional growth of team members by encouraging continuous learning and adoption of advanced data technologies, fostering cross-functional collaboration and leadership development.
Data Engineer
•Data Engineering Bootcamp
Apr 2024 - Present•Remote
Developed comprehensive data engineering solutions through hands-on projects covering modern data stack technologies, cloud platforms, and data pipeline architectures.
Key Achievements
- Designed and implemented a multi-stage ELT pipeline for Spotify data using AWS S3, DuckDB, dbt, and Airflow, following the "poor man's data lake" concept with Raw, Bronze, Silver, and Gold stages for sequential data processing and analytics-ready datasets.
- Built a comprehensive data pipeline for Adventure Works SAP data using dbt Core and BigQuery, implementing a three-layer architecture (staging, intermediate, marts) that processed 64 source tables into analytics-ready dimensional models with automated testing and documentation.
- Developed an E-commerce data pipeline extracting data from BigQuery public datasets, validating with Pydantic models for data quality assurance, and loading into DuckDB with support for multiple output destinations including CSV, S3, and Motherduck.
- Implemented infrastructure as code using Terraform to provision and manage cloud resources, ensuring consistent and reproducible data platform setups across development and production environments.
- Orchestrated automated data workflows using Apache Airflow and Astronomer, enabling daily batch processing, task scheduling, and pipeline monitoring for reliable data extraction, transformation, and loading operations.
- Created and maintained dbt data models with comprehensive testing, documentation, and version control, following modern data engineering best practices for scalable and maintainable data transformation pipelines.
- Worked with diverse database technologies including PostgreSQL, MySQL, DuckDB, and BigQuery, implementing OLTP and OLAP architectures for transactional and analytical workloads.
- Developed Python-based ETL pipelines for data ingestion from APIs, web scraping, and file systems, implementing data validation, error handling, and workflow automation for reliable data processing.
- Implemented predictive modeling and machine learning pipelines using Apache Spark, processing large-scale datasets and training Random Forest models for data-driven insights and decision-making.
- Containerized data engineering applications using Docker, enabling consistent development environments and simplified deployment workflows for data pipelines and database management.
Project Manager
•CERTI Foundation – Sustainable Energy Center
Jul 2021 - Mar 2024•Florianópolis, Brazil
Developed and executed project strategies aligned with organizational goals and market dynamics, specializing in the energy sector.
Key Achievements
- Drove a 30% boost in project efficiency by strategically implementing two Business Intelligence solutions, fostering cross-project synergy and streamlined data analysis.
- Optimized project life cycle management efficiency by introducing agile and waterfall methodologies, ensuring the delivery of projects within the allocated resources and timeframe.
- Enhanced workflow efficiency by 40% using project management and data visualization tools, including Jira, Microsoft Project and Power BI.
- Boosted the average revenue per resource by 60%, achieving this by proposing a new data modeling approach to streamline workflows and optimize resource allocation.
- Strengthened alignment between product development and strategic goals by 25% through market-driven priority setting and strategic direction.
- Led and optimized Scrum events, including Sprint Planning, Daily Stand-ups, and Sprint Reviews, championing agile principles to enhance team agility and project responsiveness.
Project Analyst
•CERTI Foundation – Sustainable Energy Center
Aug 2019 - Jul 2021•Florianópolis, Brazil
Analyzed and managed technology projects, ensuring timely delivery and stakeholder satisfaction.
Key Achievements
- Boosted project efficiency and delivery by 30% by implementing project management planning and scheduling methodologies.
- Collected and analyzed relevant data to inform decision-making and project strategies, improving alignment with stakeholder requirements.
- Increased project success rates by 25%, by effectively communicating with stakeholders and maintaining strong relationships.
- Skillfully steered and timely delivered over 48 technology initiatives, leveraging advanced project management strategies to ensure adherence to deadlines and quality standards.
Education
Pontificia Universidade Católica - Minas Gerais
Data Engineering, Postgraduate Degree
Brazil
2024
University of Alberta
Software Product Management, Specialization
Alberta, Canada
2023
Federal University of Santa Maria
Bachelor of Engineering, Production Engineering
Santa Maria, Brazil
2020
Certifications
Analytics Engineer Certificate by Indicium Academy
Comprehensive data engineering certification focusing on modern data stack tools.
- Developed comprehensive data models using dbt Core and BigQuery for the Adventure Works dataset.
- Implemented a multi-layer data architecture with staging, intermediate, and mart layers following data engineering best practices.
- Created automated testing and documentation for data models, ensuring data quality and reliability.
IBM Data Engineering Professional Certificate
Professional certificate covering end-to-end data engineering practices.
- Developed working knowledge of NoSQL & Big Data using MongoDB, Cassandra, Cloudant, Hadoop, Apache Spark, Spark SQL, Spark ML and Spark Streaming.
- Created, designed and managed relational databases such as MySQL, PostgreSQL and IBM Db2.
- Implemented ETL & Data Pipelines with Bash, Airflow & Kafka.
IBM Data Science Professional Certificate
Comprehensive data science certification covering the full data science lifecycle.
- Practiced with most up-to-date skills that data scientists use in their daily roles.
- Imported and cleaned data sets, analyzed data and built ML models and pipelines.
- Learned the tools, languages and libraries used by data scientists, including Python and SQL.
Software Product Management
Specialization in software product management methodologies and practices.
- Applied product management techniques to industry inspired scenarios.
- Interacted with clients and managed a team of developers.
- Mastered agile software development practices.
Skills
Data Platform & Architecture
Extensive experience in designing and implementing modern data platforms from scratch in cloud environments (AWS, GCP, Azure), including data lakes, data warehouses, and data marts.
Proven track record in migrating legacy data systems to modern architectures, implementing robust data governance frameworks, and ensuring data quality and reliability.
Expertise in implementing and optimizing data platforms using tools like dbt, Dagster, Airflow, Snowflake, and Databricks, with a focus on scalability and performance.
Strong experience in data modeling, ETL/ELT processes, and data pipeline development, ensuring efficient data flow and transformation.
Technical Skills
Programming Languages
PythonSQL
Data Engineering
dbtAirflowDagsterSparkKafka
Cloud Platforms
AWSGCPAzure
Databases
SnowflakeBigQueryPostgreSQLMySQLDuckDB
Data Visualization
Power BILookerStreamlit
AI/ML
TensorFlowPyTorchScikit-learn
DevOps
DockerTerraformGit
Data Product Development
Successfully delivered multiple data products including AI/ML solutions, intelligent agents, and generative AI applications, driving significant business value.
Experience in developing and implementing data strategies for enterprise clients, with a focus on pharmaceutical and healthcare sectors.
Proven ability to lead cross-functional teams in developing and deploying data products, from concept to production.
Strong background in data visualization and dashboard development using tools like Power BI, Looker, and Streamlit.
Languages
English (Fluent)Portuguese (Native)Spanish (Intermediate)