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( 10 Students )
Modern Data Stack Mastery: dbt, Fivetran, Snowflake & Airflow
Master the core tools of the modern data stack to build scalable, automated, and analytics-ready data pipelines.
Course Duration: 10 Hours
Preview Modern Data Stack Mastery: dbt, Fivetran, Snowflake & Airflow course
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Modern Data Stack Mastery: dbt, Fivetran, Snowflake & Airflow – Online Course
The landscape of data engineering has shifted dramatically from monolithic ETL pipelines to a modular, cloud-native Modern Data Stack (MDS) that separates concerns and maximizes automation, scalability, and speed. This course, Modern Data Stack Mastery: dbt, Fivetran, Snowflake & Airflow, is designed to help data professionals, analysts, and engineers build an end-to-end, best-practice data pipeline using the most in-demand tools in today’s ecosystem.
The course introduces you to the four key components of the modern data stack:
- Fivetran for fully-managed, no-code data ingestion
- Snowflake as the scalable cloud data warehouse
- dbt (data build tool) for modular transformation using SQL and version control
- Apache Airflow for orchestrating and automating workflows
Fivetran is a fully-managed ELT (Extract, Load, Transform) platform that automates data ingestion from various sources (databases, SaaS apps, APIs, files, etc.) into a destination like a data warehouse or data lake. It is no-code/low-maintenance, meaning connectors are prebuilt, schema changes are handled automatically, and data pipelines stay in sync without manual effort. This lets teams focus on analysis rather than building and maintaining ETL jobs.
Snowflake is a cloud-native data warehouse designed for scalable storage and compute. It separates storage, compute, and services layers, enabling independent scaling, high concurrency, and pay-as-you-go pricing. Snowflake supports structured and semi-structured data (JSON, Parquet, Avro) and provides built-in features like secure data sharing, role-based governance, and automatic scaling. It runs on major clouds (AWS, Azure, GCP), making it popular for enterprises adopting a modern data architecture.
dbt is a transformation framework that lets data teams write modular SQL-based transformations directly in the data warehouse (e.g., Snowflake, BigQuery, Redshift). It brings software engineering best practices into analytics engineering, including:
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Version control (Git integration)
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Testing and documentation
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Dependency management between models
This ensures transformations are maintainable, testable, and collaborative, reducing the risks of ad-hoc SQL scripts scattered across teams.
Apache Airflow is an open-source workflow orchestration tool used to schedule, monitor, and manage complex data pipelines. It represents workflows as DAGs (Directed Acyclic Graphs) written in Python, giving flexibility to define dependencies, retries, and schedules. Airflow integrates with multiple systems (databases, cloud services, APIs) and is widely used for ETL orchestration, machine learning workflows, and automation in modern data platforms.
⚡Together, these tools form a modern data stack:
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Fivetran → Ingest raw data
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Snowflake → Store and scale data
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dbt → Transform data into analytics-ready models
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Airflow → Orchestrate and automate the entire workflow
By combining these tools, you'll learn to create a data pipeline that ingests raw data from diverse sources (SaaS apps, databases), transforms it into clean, analytics-ready tables using dbt, stores it efficiently in Snowflake, and schedules it via Airflow. You’ll also explore CI/CD practices, testing, documentation, and lineage tracking—everything required for a production-grade data stack.
What is the Modern Data Stack?
The Modern Data Stack is a composable set of tools and platforms that replace legacy ETL workflows. It emphasizes modularity, cloud-first operations, and analytics-centric design. Rather than writing custom scripts, teams now orchestrate pipelines with Airflow, extract data with Fivetran, transform it with dbt, and store it in scalable warehouses like Snowflake or BigQuery.
By the end of this course, you’ll gain practical mastery of each tool and understand how they integrate to enable modern, reliable data engineering workflows.
Course/Topic 1 - Coming Soon
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The videos for this course are being recorded freshly and should be available in a few days. Please contact info@uplatz.com to know the exact date of the release of this course.
Course Objectives Back to Top
Upon completion of this course, learners will be able to:
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Understand the architecture and philosophy of the Modern Data Stack.
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Set up fully automated ELT pipelines using Fivetran for data extraction.
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Use Snowflake as a performant, secure, and cost-efficient data warehouse.
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Build modular data models using dbt’s SQL + Jinja templating framework.
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Write tests, document models, and manage dbt projects with version control.
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Create and deploy DAGs using Apache Airflow to orchestrate workflows.
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Monitor data pipelines, track failures, and manage retries with Airflow UI.
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Integrate CI/CD pipelines to automate testing and deployment of dbt projects.
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Understand data lineage, dependencies, and collaboration through dbt Docs.
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Apply best practices for scalable, maintainable analytics engineering.
Course Syllabus Back to Top
Course Syllabus
Module 1: Introduction to the Modern Data Stack
- Overview of traditional vs. modern data architectures
- Key benefits of decoupling ingestion, transformation, and orchestration
- Tool comparison: Fivetran, dbt, Airbyte, Snowflake, BigQuery, Airflow
Module 2: Data Ingestion with Fivetran
- Introduction to Fivetran and managed ELT
- Setting up connectors (PostgreSQL, Salesforce, Google Sheets)
- Incremental syncs, schema drift handling, and connector management
Module 3: Cloud Data Warehousing with Snowflake
- Snowflake architecture (virtual warehouses, scaling, caching)
- Loading data from Fivetran into raw schemas
- Query performance tuning, security, and roles
Module 4: Data Modeling with dbt Core
- dbt concepts: models, seeds, snapshots, sources
- Jinja templating and model configurations
- Writing modular transformations (staging, intermediate, marts)
Module 5: dbt Testing, Documentation & Deployment
- Writing data tests (unique, not null, accepted values)
- Auto-generating dbt Docs and lineage graphs
- dbt Cloud vs. dbt Core
- Using Git for version control
Module 6: Workflow Orchestration with Apache Airflow
- DAG creation, operators, sensors, task dependencies
- Triggering dbt runs and data checks
- Retry logic, SLAs, failure alerts
Module 7: Project – Sales Analytics Pipeline
- Ingest sales data using Fivetran
- Model in dbt with clean, tested schemas
- Schedule and monitor pipeline with Airflow
- Visualize with dbt Docs and Snowflake dashboarding tools
Module 8: CI/CD and Team Collaboration
- Github Actions for dbt testing
- Branching, pull requests, and code reviews
- Managing environments and roles
Module 9: Advanced Topics
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Incremental models and partitioning strategies
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SCD (Slowly Changing Dimensions) with dbt snapshots
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Cost management in Snowflake
Certification Back to Top
Upon successful completion of this course, you will earn the Uplatz Certificate in Modern Data Stack Engineering, a professional credential that validates your expertise in integrating, modeling, and automating data workflows using modern tools like dbt, Fivetran, Snowflake, and Apache Airflow.
This certification demonstrates your ability to construct production-grade pipelines with best practices in data transformation, version control, orchestration, testing, and documentation. Unlike traditional ETL certifications, this credential highlights your command of modular, cloud-native solutions that are now central to the work of analytics engineers and data platform teams.
Whether you’re looking to break into data engineering, accelerate your current role, or showcase your capability in building scalable data infrastructure, this certificate sets you apart as a practitioner who is fluent in today’s most in-demand tools and practices in the data world.
Career & Jobs Back to Top
The Modern Data Stack (MDS) is now the industry standard in data teams across startups, enterprises, and consultancies. Companies are replacing legacy ETL workflows with modular, scalable stacks that rely on Snowflake, dbt, Airflow, and Fivetran.
This course prepares you for high-growth roles such as:
- Analytics Engineer
- Data Engineer (Modern Stack)
- Data Platform Engineer
- ETL/ELT Developer (Cloud)
- Snowflake + dbt Consultant
- Data Infrastructure Specialist
Organizations in finance, healthcare, e-commerce, SaaS, and logistics are rapidly building real-time analytics layers and self-serve data platforms. With this training, you’ll be able to join or lead those initiatives with confidence.
You’ll gain fluency not only in building robust data pipelines but also in adopting engineering best practices like CI/CD, version control, documentation, testing, and collaboration. Whether you're aiming for a promotion, transitioning into data from another role, or consulting on analytics modernization projects, this skillset is a powerful career accelerator.
Freelancers and independent contractors can also use these tools to offer rapid, scalable solutions to clients looking to implement a modern data stack.
Interview Questions Back to Top
1. What is the Modern Data Stack and why is it important?
The Modern Data Stack is a modular set of cloud-based tools used for data ingestion, transformation, orchestration, and storage. It enables agile, scalable, and maintainable data pipelines.
The Modern Data Stack is a modular set of cloud-based tools used for data ingestion, transformation, orchestration, and storage. It enables agile, scalable, and maintainable data pipelines.
2. What is Fivetran used for?
Fivetran is a managed ELT tool that automatically syncs data from source systems to destinations like Snowflake, handling schema changes and incremental loads.
Fivetran is a managed ELT tool that automatically syncs data from source systems to destinations like Snowflake, handling schema changes and incremental loads.
3. How does dbt differ from traditional ETL tools?
dbt focuses only on the transformation layer using SQL, allowing data engineers and analysts to build modular, tested models with version control.
dbt focuses only on the transformation layer using SQL, allowing data engineers and analysts to build modular, tested models with version control.
4. What is the benefit of using Airflow in a modern pipeline?
Airflow provides scheduling, dependency management, and monitoring of workflows. It helps automate data pipeline execution and alerting.
Airflow provides scheduling, dependency management, and monitoring of workflows. It helps automate data pipeline execution and alerting.
5. What are dbt models and how are they structured?
dbt models are SQL files that define transformations. They can be layered as staging, intermediate, and marts for clarity and reusability.
dbt models are SQL files that define transformations. They can be layered as staging, intermediate, and marts for clarity and reusability.
6. What is a DAG in Airflow?
A DAG (Directed Acyclic Graph) defines a workflow consisting of tasks and their dependencies that are executed in a specific order.
A DAG (Directed Acyclic Graph) defines a workflow consisting of tasks and their dependencies that are executed in a specific order.
7. How does Snowflake scale for large workloads?
Snowflake uses virtual warehouses that auto-scale compute separately from storage, allowing for concurrency and fast query execution.
Snowflake uses virtual warehouses that auto-scale compute separately from storage, allowing for concurrency and fast query execution.
8. How do you ensure data quality in dbt?
By writing tests (unique, not null, relationships) and automating them in CI/CD to catch schema and logic issues early.
By writing tests (unique, not null, relationships) and automating them in CI/CD to catch schema and logic issues early.
9. What is the difference between ELT and ETL?
ETL transforms data before loading it into the warehouse, while ELT loads raw data first and transforms it within the warehouse.
ETL transforms data before loading it into the warehouse, while ELT loads raw data first and transforms it within the warehouse.
10. How do you orchestrate dbt jobs using Airflow?
By creating DAGs that trigger dbt CLI commands using Bash or Python operators, handling retries, monitoring, and alerts.
By creating DAGs that trigger dbt CLI commands using Bash or Python operators, handling retries, monitoring, and alerts.
Course Quiz Back to Top
FAQs
Back to Top
Q1. What are the payment options?
A1. We have multiple payment options:
1) Book your course on our webiste by clicking on Buy this course button on top right of this course page
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A2. Yes, you will receive course completion certificate from Uplatz confirming that you have completed this course with Uplatz. Once you complete your learning please submit this for to request for your certificate https://training.uplatz.com/certificate-request.php
Q3. How long is the course access?
A3. All our video courses comes with lifetime access. Once you purchase a video course with Uplatz you have lifetime access to the course i.e. forever. You can access your course any time via our website and/or mobile app and learn at your own convenience.
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A4. Video courses cannot be downloaded, but you have lifetime access to any video course you purchase on our website. You will be able to play the videos on our our website and mobile app.
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A5. We do not take exam as part of the our training programs whether it is video course or live online class. These courses are professional courses and are offered to upskill and move on in the career ladder. However if there is an associated exam to the subject you are learning with us then you need to contact the relevant examination authority for booking your exam.
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Our yearly subscription gives you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews every year. Minimum committment is for 1 year, you can cancel the plan anytime after 1 year.
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A16. Software access can be purchased seperately at an additional cost. The cost varies from course to course but is generally in between GBP 20 to GBP 40 per month.
Q17. Does your course guarantee a job?
A17. Our course is designed to provide you with a solid foundation in the subject and equip you with valuable skills. While the course is a significant step toward your career goals, its important to note that the job market can vary, and some positions might require additional certifications or experience.
Remember that the job landscape is constantly evolving. We encourage you to continue learning and stay updated on industry trends even after completing the course. Many successful professionals combine formal education with ongoing self-improvement to excel in their careers. We are here to support you in your journey!
Q18. Do you provide placement services?
A18. While our course is designed to provide you with a comprehensive understanding of the subject, we currently do not offer placement services as part of the course package. Our main focus is on delivering high-quality education and equipping you with essential skills in this field.
However, we understand that finding job opportunities is a crucial aspect of your career journey. We recommend exploring various avenues to enhance your job search:
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b) Networking: Attend industry events, workshops, and conferences to build connections with professionals in your field. Networking can often lead to job referrals and valuable insights.
c) Online Professional Network: Leverage platforms like LinkedIn, a reputable online professional network, to explore job opportunities that resonate with your skills and interests.
d) Online Job Platforms: Investigate prominent online job platforms in your region and submit applications for suitable positions considering both your prior experience and the newly acquired knowledge. e.g in UK the major job platforms are Reed, Indeed, CV library, Total Jobs, Linkedin.
While we may not offer placement services, we are here to support you in other ways. If you have any questions about the industry, job search strategies, or interview preparation, please dont hesitate to reach out. Remember that taking an active role in your job search process can lead to valuable experiences and opportunities.
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Q21. Can I get help from a tutor if I have doubts while learning from a video course?
A21. Tutor support is not available for our video course. If you believe you require assistance from a tutor, we recommend considering our live class option. Please contact our team for the most up-to-date availability. The pricing for live classes typically begins at USD 999 and may vary.