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    Databricks Data Engineer

    Become a Certified Databricks Data Engineer with Tech Skill School

    Elevate your career in data engineering with our comprehensive Databricks Data Engineer course. At Tech Skill School, we offer an in-depth training program designed to equip you with the skills and knowledge needed to excel in data engineering roles, utilizing the powerful Databricks platform.

    Why Enroll in Our Databricks Data Engineer Course?

    • Industry-Experienced Trainers: Learn from professionals not just trainers. Experts with 14 years of real-world experience in data engineering and analytics. Our trainers bring extensive knowledge and practical insights to the classroom.
    • Hands-On Learning: Engage in real-life projects and challenges that our trainers encounter in their everyday work. This practical approach ensures you gain valuable, job-ready skills.
    • Job-Focused Training: Our curriculum targets specific job profiles. We provide all the hands-on training necessary to help you secure a position as a Databricks Data Engineer.
    • Comprehensive Support: From enrollment to course completion, you’ll have access to a range of resources and support, including a dedicated support team, extensive learning materials, and active community forums.

    KEY FEATURES

    70 hours Instructor
    led live training

    Personal lab
    setup

    Job Oriented
    content

    Recorded
    Sessions

    Technical
    Support

    | Overview of SOC & its structure

    1. Introduction to Databricks platform
    2. Key features and components
    3. Navigating the Databricks workspace
    1. Introduction to SQL and its importance
    2. Basic SQL commands and queries
    3. Advanced SQL techniques
    4. Optimizing SQL queries for performance
    1. Basics of Python programming
    2. Key libraries for data manipulation
    3. Writing efficient Python code for Spark
    4. Debugging and troubleshooting Python scripts
    1. Creating and configuring Databricks clusters
    2. Navigating the Databricks workspace
    3. Connecting to data sources
    1. Ingesting data from various sources
    2. Data transformation and cleaning techniques
    3. Working with structured and unstructured data
    1. Designing and managing data pipelines
    2. Automating workflows with Databricks
    3. Scheduling and monitoring data jobs
    1. Introduction to Delta Lake
    2. Creating and managing Delta tables
    3. Delta Lake features and benefits
    4. Using Delta Lake for data versioning and time travel
    1. Creating and manipulating DataFrames
    2. DataFrame operations and transformations
    3. Working with large datasets using DataFrames
    4. Optimizing DataFrame performance
    1. Understanding data transformation concepts
    2. Common data transformation techniques
    3. Implementing transformations in Spark
    4. Performance tuning for data transformations
    1. Introduction to incremental data processing
    2. Techniques for processing incremental data
    3. Implementing incremental data pipelines
    4. Monitoring and managing incremental data workflows
    1. Introduction to ELT (Extract, Load, Transform)
    2. Writing Spark SQL queries for ELT
    3. Using Python for data transformation
    4. Integrating Spark SQL and Python for ELT
    1. Designing robust production data pipelines
    2. Automating data workflows
    3. Monitoring and managing production pipelines
    4. Best practices for pipeline maintenance
    1. Importance of data governance
    2. Implementing data governance policies
    3. Managing data access and security
    4. Ensuring compliance with data regulations
    1. Integrating Databricks with other data services (e.g., Github, PowerBi)
    2. Connecting to data storage solutions (e.g., Azure Blob Storage)
    3. Real-time data integration with streaming services
    1. Applying learned concepts to a real-world project
    2. Designing and implementing a data pipeline
    3. Presenting project findings and results
    4. Receiving feedback and improving the project
    1. Resume writing & best practices
    2. LinkedIn Profile optimization
    3. Mock Interviews

    Career Opportunities

    Completing the Databricks Data Engineer course opens up numerous career opportunities in data engineering and analytics. Potential job roles include:

    • Databricks Data Engineer
    • Data Pipeline Developer
    • Data Analyst
    • Big Data Engineer
    • Machine Learning Engineer

    About Us

    Tech Skill School is an online learning platform committed to providing high-quality education and professional development in the field of technology. Our goal is to help individuals gain the skills necessary to excel in their careers and meet the demands of the ever-evolving tech industry.

    Contact

    Australia - HQ

    46 Hoskins Street Canberra, ACT

    info@techskillschool.com

    +61423002099

    India - HQ

    305 Waghawadi Road, Bhavnagar, Gujarat

    admin@techskillschool.com

    +91-9512026616

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