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Advanced Certification in Data Engineering with GenAI

Live Online (VILT) & Classroom Corporate Training Program

Master modern data engineering on the Lakehouse - Spark, Delta Lake, pipelines, governance, Azure integration and GenAI/Agentic data engineering.

Expert-Led VILT & Classroom Multi-Course Certification Program Level: Intermediate to Advanced Certificate of Completion
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Overview

Master modern data engineering on the Lakehouse - Spark, Delta Lake, pipelines, governance, Azure integration and GenAI/Agentic data engineering.

What You Will Learn

By the end of this course, learners will be able to:

  • Engineer batch and streaming data pipelines with Apache Spark and Delta Lake.
  • Design Lakehouse data models and orchestrate production pipelines with Lakeflow and Databricks Workflows.
  • Apply Unity Catalog governance, CI/CD and Azure integration for production data platforms.
  • Build RAG, context-engineering and agentic GenAI solutions for data engineering.

Prerequisites

Familiarity with SQL and Python is recommended. A foundational understanding of databases and cloud concepts is helpful.

Course Outline

Course 1: Foundations of AI-Era Data Engineering with Spark & Delta Lake

  • Data Warehouse Evolution
  • Lakehouse Architecture
  • Data Intelligence Platform
  • DE Lifecycle Stages
  • ETL vs ELT
  • Batch vs Streaming
  • Data Engineer Roles & Responsibilities
  • Modern Data Stack Overview
  • Data Lake vs Data Warehouse vs Lakehouse
  • Data Governance Basics
  • Industry Use Cases & Career Paths

  • Control-Data Plane
  • Workspace Architecture
  • Unity Catalog Overview
  • Compute Types
  • SQL Warehouses
  • Cluster Configuration
  • Cluster Policies
  • Notebooks & Repos
  • Databricks Runtime Versions
  • Workspace Navigation & Collaboration Tools

  • Spark Architecture
  • Driver & Executors
  • DAG Scheduler
  • RDDs vs DataFrames
  • Transformations vs Actions
  • Lazy Evaluation
  • PySpark DataFrame API
  • Reading & Writing Data with Spark
  • Partitioning Basics
  • SparkSession & SparkContext
  • Broadcast Variables & Accumulators

  • Spark SQL Interop
  • Join Strategies
  • Repartition vs Coalesce
  • Caching Strategies
  • Spark UI Basics
  • DAG Visualization
  • Adaptive Query Execution (AQE)
  • Identifying & Fixing Data Skew
  • Common Performance Anti-Patterns

  • Delta Transaction Log
  • ACID on Lakehouse
  • Schema Enforcement
  • Schema Evolution
  • Time Travel
  • OPTIMIZE & Z-Order
  • VACUUM & Data Retention
  • MERGE / UPSERT Operations
  • Delta Table Constraints
  • Liquid Clustering
  • Delta Sharing Basics

  • Full/Incremental Load
  • COPY INTO Basics
  • Idempotent Ingestion
  • Auto Loader
  • Schema Inference/Evolution
  • Rescued Data Column
  • File Notification vs Directory Listing Mode
  • Handling Malformed Records
  • Batch Ingestion Error Recovery

Course 3: Lakehouse Pipelines, Modeling & Orchestration

  • Structured Streaming Basics
  • Sources, Sinks, Triggers
  • Windowing & Watermarking
  • Stateful Aggregations
  • Change Data Feed
  • CDC Merge Patterns
  • Checkpointing & Fault Tolerance
  • Exactly-Once Processing Guarantees

  • Medallion Layers
  • Data Contracts
  • Dimensional Modeling
  • SCD via MERGE
  • Data Vault Concepts
  • Star Schema Comparison
  • Bronze/Silver/Gold Design Patterns
  • Fact & Dimension Table Design
  • Modeling for BI vs ML Consumption

  • Declarative Pipelines
  • Streaming Tables/MVs
  • Pipeline DAG Design
  • Data Quality Expectations
  • Dev/Prod Modes
  • Event Logs/Lineage
  • Pipeline Triggers & Scheduling
  • Data Quality Alerting & Quarantine Patterns

  • Lakeflow Jobs Overview
  • Task Types
  • dbt Job Task
  • Task Dependencies
  • Conditional Execution
  • Job/Shared Clusters
  • Job Parameters & Variables
  • Retry Policies & Failure Alerting
  • Job Scheduling & Triggers
  • Monitoring Job Runs
  • Multi-Task Workflow Design Patterns

Course 4: Governance, Production Engineering & Azure Integration

  • UC Metastore Hierarchy
  • Managed/External Tables
  • GRANT/REVOKE Access
  • Row-Level Security
  • Column Masking
  • Tags & ABAC
  • Data Lineage Tracking
  • PII Classification
  • Audit Logging
  • Catalog/Schema Design Patterns
  • Delta Sharing via Unity Catalog
  • Metric Views & Certified Metrics
  • Access Governance Best Practices

  • Git Branching Strategy
  • CLI Deep Dive
  • Asset Bundles (DABs)
  • Environment Targets
  • CI/CD Integration
  • PR Review Workflows
  • GitHub Actions for Databricks
  • Automated Testing for Pipelines
  • Deployment Promotion (Dev -> Staging -> Prod)
  • Rollback & Release Management

  • File Sizing
  • Predictive I/O
  • Photon Engine
  • Lakehouse Monitoring
  • System Tables (Billing)
  • Cost Optimization
  • Cluster Right-Sizing
  • Query Profiling & Diagnostics
  • FinOps Best Practices for Data Platforms

  • Workspace Deployment
  • Pricing Tiers
  • VNet/Private Link
  • Network Security Groups
  • Entra ID Integration
  • Secret Scopes
  • Identity & Access Management (IAM)
  • Compliance & Security Baselines

  • ADLS Gen2 Basics
  • External Locations
  • Azure Data Factory
  • ADF/Lakeflow Jobs
  • Log Analytics
  • Cross-Platform Cost Mgmt
  • Hybrid Orchestration Patterns (ADF + Databricks)

Course 5: GenAI & Agentic Data Engineering

  • GenAI Landscape
  • Foundation Models
  • Prompt Engineering Basics
  • Mosaic AI APIs
  • Unstructured Data Ingestion
  • Chunking Strategies
  • Embeddings Overview
  • Model Serving Endpoints
  • Tokens & Context Windows
  • Data Preparation for LLM Pipelines

  • Context vs Prompting
  • Context Pillars
  • Context Offloading
  • Compression Techniques
  • Context Isolation
  • Agent Memory Patterns
  • Tool-Use Context Design
  • Unity AI Gateway Overview
  • MCP Fundamentals
  • Context Governance & Guardrails
  • Evaluating Context Quality

  • Catalog as Decision-Maker
  • Business Semantics Layer
  • Glossary & Domains
  • Genie Ontology
  • Knowledge Graphs
  • Entity Resolution
  • Metric Definitions & Governance
  • Semantic Layer Design Patterns

  • RAG Architecture
  • Vector Search Index
  • Embedding Pipeline Design
  • Chunking for Retrieval
  • Vector Index Governance
  • RAG Evaluation
  • Hybrid Search (Keyword + Vector)

  • Agentic AI Concepts
  • Mosaic Agent Framework
  • Agent Bricks
  • Agent Use Cases
  • Genie AI/BI Spaces
  • LLMOps Basics
  • Agent Tool Design & Function Calling
  • Guardrails for Agentic Workflows
  • Monitoring & Debugging Agent Behavior

The Synergific Advantage

Why enterprise teams pick Synergific.

Authorised curriculum is the floor — not the differentiator. What sits above it is what gets renewed.

500+Enterprises served
50+OEM partnerships
1,100+Exam vouchers
< 4 hSolutions reply
01

Live Hands-On Cloud Labs

Every course ships with 24/7 access to production-grade AWS, Azure, GCP and OCI environments. Real consoles, real workloads, the bills handled by us.

→ 02

Hire-Train-Deploy

We source, train, and deploy certified engineers on your project. Single contract, billable from week one, replacement guarantee on attrition.

→ 03

Four-Hour Solutions SLA

Direct line to a senior solutions advisor — not a ticket queue, not an offshore desk. Reply within four business hours, every time.

→ 04

Voucher-Backed Certification

1,100+ exam vouchers from 50+ OEMs at enterprise pricing. Most certifications include retake protection — success measured after the exam.

→ 05

Authorised Curriculum, Local Delivery

Microsoft Solutions Partner, AWS APN, Red Hat, Cisco, Oracle, EC-Council, PECB and more. Exact official content delivered with our trainers, our labs, our SLA.

→

Available Training Modes

Pick the format that fits your team.

Same authorised curriculum, same trainers, same hands-on cloud labs — delivered the way that works for you.

Live Online (VILT)

Real-time instructor-led sessions over Zoom or Teams. Same classroom, different time zones.

Most popular

Classroom

Face-to-face training delivered at your office, our Bengaluru centre, or any partner venue worldwide.

Onsite

Self-Paced

Recorded sessions plus 24/7 access to cloud labs and assessments. Learn at the pace that works for each engineer.

On-demand

Blended

Live workshops with self-paced reinforcement and project-based labs. Best for hybrid teams across regions.

Hybrid teams
All modes include: hands-on cloud labs, recordings, assessments, certificate of completion. Talk to a solutions advisor →

Our Training Process

How a course becomes measurable skill.

One contract, five steps, zero handoffs. From discovery to deployment, the same Synergific team owns the outcome — not a chain of vendors.

5 Steps from your scoping call to certified, productive engineers.
01

Discover & set goals

We start with a scoping call to understand your team's current skill level, target outcomes, deadlines, and certification needs — then translate that into a measurable success plan with named owners on both sides.

02

Curate the right path

We map the optimal learning path — instructor-led, self-paced, or blended — with hands-on cloud labs, prerequisite refreshers, and certification vouchers built in. No filler modules, no padded curriculum.

03

Deliver hands-on training

Authorised trainers run live sessions backed by 24/7 cloud labs and real-world projects. Theory and practice on the same day — learners stop forgetting concepts before they get to apply them.

04

Assess & mentor

Continuous skill checks, mock exams, and 1:1 mentoring keep the program honest. If anyone falls behind, we course-correct in-flight — you'll never find out at the end that two engineers couldn't keep up.

05

Certify & apply on the job

Voucher-backed certification, post-training office hours, and 30-day reinforcement so skills land on real work — not just on the exam scorecard. Success measured after the course ends, not before.

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