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Professional Data Engineer Training
Live Online & Classroom Enterprise Training
Learners progress through a series of courses, labs, and practical projects, learning how to design, build, monitor, and optimize data pipelines on Google Cloud. Modules include building batch and streaming pipelines, working with Dataflow, modernizing data warehouses and lakes, using BigQuery, and integrating generative AI with data workflows. By the end, participants will have experience across the full spectrum of data engineering tasks on GCP.
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What is Professional Data Engineer Training about?
What are the objectives of Professional Data Engineer Training ?
Who is Professional Data Engineer Training for?
What are the prerequisites for Professional Data Engineer Training?
Available Training Modes
Live Online Training
10 DaysSelf-Paced Training
100 HoursCourse Outline Expand All
Expand All
- Access and navigate GCP console (Projects, Resources)
- Explore IAM users, roles, permissions
- Enable and use APIs in GCP
- Basic hands-on tasks to familiarize with Google Cloud environment
- Overview of domains in the Professional Data Engineer exam
- Create personalized study plan aligned to weak areas
- Assess readiness and identify knowledge gaps
- Guidance on certification strategy and exam format
- Roles/responsibilities of data engineers and mapping to business needs
- Challenges in data pipelines, data movement, scale, reliability
- Google Cloud offerings for data engineering (Dataflow, Dataproc, BigQuery)
- Strategies to mitigate common data engineering challenges
- Distinguish data lakes vs. data warehouses and their use cases
- Evaluate and use GCP storage and warehousing solutions (BigQuery, Cloud Storage, etc.)
- Migrate or integrate existing systems (on-prem, Hadoop, Spark) into GCP
- Best practices in data lifecycle, governance, partitioning, storage layout
- Understand paradigms: EL, ELT, ETL and when to use each
- Use Dataflow, Dataproc, or managed compute for batch workloads
- Optimize transformations, data partitioning, sharding, joins
- Monitor, debug, and scale batch jobs in production
- Use Pub/Sub for real-time data ingestion
- Windowing, watermarking, event time processing in streaming systems
- Integration with Dataflow for streaming pipelines
- Fault tolerance, retry, latency, and throughput considerations
- Introduction to Apache Beam model and its concepts
- Relationship between Beam and Dataflow
- Basic transformations (ParDo, GroupByKey, windowing)
- Running simple pipelines using Dataflow model
- Advanced Beam SDK programming constructs
- Handling streaming + batch hybrid logic
- State, timers, side inputs/outputs, triggers in Beam
- Testing, deploying, and versioning pipelines
- Pipeline lifecycle, deployment, and management strategies
- Monitoring, metrics, logs, and troubleshooting pipelines
- Performance tuning, autoscaling, resource allocation
- Reliability, retries, failure handling, idempotence
- Create tables, partitions, clustering in BigQuery
- Work with JSON, arrays, structs, nested fields
- Query optimization, joins, union, window functions
- Performance tuning and cost management in BigQuery
- Fundamentals of a data mesh architecture
- Use Dataplex to manage data domains, governance, cataloging
- Data security, access, and policy enforcement in Dataplex
- Integration of data mesh with analytics and pipelines
- Use AI-assisted features for query generation and optimization
- Data exploration and auto-insights in BigQuery with Gemini
- Code generation, suggestions, and debugging assistance
- Visualizations and workflow discovery leveraging AI tools
- Use generative AI models in BigQuery environment
- Solve a business use case using Gemini & data workflows
- Train, inference, and integration of Gemini models with data sets
- Evaluate outputs, refine prompts, manage model usage costs
Who is the instructor for this training?
The trainer for this Professional Data Engineer Training has extensive experience in this domain, including years of experience training & mentoring professionals.
Professional Data Engineer Training - Certification & Exam
After completing this course, you can take the below certifications: Google Cloud Professional Data Engineer Certification
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