Pipeline Development
Design, build, and maintain dependable dbt-enabled data pipelines that automate collection, transformation, testing, and delivery, helping teams trust the data powering dashboards, reports, and analytics workflows.
Strengthen your analytics engineering workflow with dbt cloud support from Dynamic Data. Our dbt Certified Developer team helps businesses build reliable models, automate transformations, improve documentation, resolve job failures, and create trustworthy data pipelines that support faster, clearer decision-making across modern data stacks.
Practical analytics engineering support for cleaner models, automated workflows, reliable pipelines, and decision-ready business data.
Design, build, and maintain dependable dbt-enabled data pipelines that automate collection, transformation, testing, and delivery, helping teams trust the data powering dashboards, reports, and analytics workflows.
Connect disparate sources into a unified analytics layer, ensuring dbt models are built on accurate, consistent, and accessible data that reduces silos across departments.
Streamline recurring transformation tasks, orchestration, and reporting dependencies so analytics teams spend less time on manual maintenance and more time delivering business insight.
Analyze model logic, query behavior, and pipeline bottlenecks to improve run times, reduce warehouse costs, and keep dbt Cloud jobs operating efficiently.
Establish naming conventions, ownership standards, documentation practices, and quality checks that make dbt projects easier to audit, scale, and maintain.
Prepare modeled data for dashboards, reports, and visual analytics, ensuring business users can access trustworthy metrics and make faster data-driven decisions.
We review your existing warehouse, source systems, dbt Cloud configuration, model structure, job history, and reporting dependencies to identify risks, bottlenecks, and opportunities for better analytics engineering practices.
Dynamic Data helps growing teams turn complex data environments into reliable decision-making systems.
"Awesome attention to detail with a very collaborative approach. A great partnership relationship, very dependable, and outstanding follow through."
Work with a multidisciplinary data team focused on practical, business-ready outcomes.
Your project is supported by professionals with proven dbt development expertise.
We combine analytics engineering, BI, AI, and governance across complex data ecosystems.
Our solutions reduce manual work and make recurring reporting processes more reliable.
Every technical improvement is mapped to clearer insights and measurable business value.
Certified data experts supporting modern analytics engineering.
CEO & Founder
Victoria Gallerano is the CEO and Founder of Dynamic Data, which she established in 2020 with a mission to transform complex data into actionable insights for businesses worldwide. A recognized expert in Business Intelligence, Artificial Intelligence, and Data Governance, Victoria founded the company to help organizations launch modern data stacks, automate reporting, and harness the power of machine learning for real, measurable results. Under her leadership, Dynamic Data has grown to a team of over 25 professionals spanning Europe, South America, and the USA. Victoria is driven by a client-centric mindset and a passion for innovation, ensuring every solution delivered is tailored to help businesses thrive in an increasingly digital world.
CTO
Diego Prinzi serves as Chief Technology Officer at Dynamic Data, where he leads a multidisciplinary team of data professionals dedicated to delivering innovative, client-driven solutions. With over 15 years of experience in software development and data engineering, Diego brings deep technical expertise and a strategic vision that empowers businesses to make smarter, faster decisions. He is passionate about translating complex data challenges into clear, actionable outcomes that drive meaningful growth for clients. Diego's collaborative leadership style and command of over 35 platforms and languages make him a cornerstone of Dynamic Data's ability to deliver cutting-edge AI and machine learning solutions across industries.
Analytics Engineer
Marcelo Bour is an Analytics Engineer at Dynamic Data and a certified dbt Developer, bringing a powerful combination of technical precision and business acumen to every project he undertakes. With a strong foundation in data modeling, workflow optimization, and analytics engineering, Marcelo plays a key role in streamlining data pipelines and reducing manual efforts for clients undergoing digital transformation. He is deeply committed to fostering collaboration across teams and aligning technical solutions with real business needs. Marcelo's ability to bridge the gap between complex data systems and practical business outcomes makes him an integral part of Dynamic Data's mission to help companies unlock the full value of their data.
dbt support helps teams design, maintain, troubleshoot, and optimize dbt projects used for analytics engineering. It can include model development, testing, documentation, job scheduling, performance tuning, source integration, and governance. Dynamic Data’s dbt Certified Developer team focuses on making transformation workflows more reliable, easier to maintain, and aligned with business reporting needs.
Talk with our analytics engineering experts about your dbt Cloud needs.
Validated expertise in dbt project development.
Quality assurance discipline for reliable delivery.
Practical expertise across advanced data platforms.
Tell us about your current data stack, workflow challenges, and reporting goals. Dynamic Data will review your needs and recommend a practical support plan.
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