{"id":28094,"date":"2026-04-13T04:20:21","date_gmt":"2026-04-13T04:20:21","guid":{"rendered":"https:\/\/www.cloudthat.com\/training\/?post_type=stm-courses&p=28094"},"modified":"2026-04-14T04:34:52","modified_gmt":"2026-04-14T04:34:52","slug":"dp-750-build-scalable-data-engineering-solutions-with-azure-databricks","status":"publish","type":"stm-courses","link":"https:\/\/www.cloudthat.com\/training\/microsoftdynamics\/dp-750-build-scalable-data-engineering-solutions-with-azure-databricks","title":{"rendered":"DP-750: Build Scalable Data Engineering Solutions with Azure Databricks"},"content":{"rendered":"

This course focuses on implementing data engineering solutions using Azure Databricks, a powerful Apache Spark-based analytics platform. Learners will gain\u00a0expertise\u00a0in building scalable data pipelines, transforming large\u00a0datasets\u00a0and managing distributed data processing workloads efficiently.<\/span>\u00a0<\/span><\/p>\n

The course emphasizes practical skills such as working with Delta Lake,\u00a0optimizing\u00a0Spark jobs, implementing structured\u00a0streaming\u00a0and integrating Databricks with Azure services. Participants will also learn best practices for performance tuning, data\u00a0governance\u00a0and\u00a0production deployment. By the end of the course, learners will be equipped to design robust, high-performance data engineering solutions suitable for enterprise-scale analytics workloads.<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

This course focuses on implementing data engineering solutions using Azure Databricks, a powerful Apache Spark-based analytics platform. Learners will gain\u00a0expertise\u00a0in building scalable data pipelines, transforming large\u00a0datasets\u00a0and managing distributed data processing workloads efficiently.\u00a0 The course emphasizes practical skills such as working with Delta Lake,\u00a0optimizing\u00a0Spark jobs, implementing structured\u00a0streaming\u00a0and integrating Databricks with Azure services. Participants will also learn […]<\/p>\n","protected":false},"author":6436,"featured_media":26908,"template":"","meta":{"footnotes":""},"stm_lms_course_taxonomy":[62],"metadata":{"stm_lms_product_id":["28095"],"_edit_lock":["1776143369:5091"],"_edit_last":["5091"],"permalink_customizer":["microsoftdynamics\/dp-750-build-scalable-data-engineering-solutions-with-azure-databricks"],"permalink_customizer_regenerate_status":["1"],"_thumbnail_id":["26908"],"popular_course":["0"],"_popular_course":["field_64253688bc2e5"],"course_banner_image":[""],"_course_banner_image":["field_63c69a6b81cf1"],"mobile_banner_image":[""],"_mobile_banner_image":["field_63cf93896d207"],"banner_link":[""],"_banner_link":["field_63c69a9681cf2"],"banner_image":[""],"_banner_image":["field_621873548f922"],"banner_description":["Learn to design and implement scalable data engineering pipelines using Azure Databricks. Master Spark, Delta Lake and structured streaming to process big data efficiently and build modern, high-performance analytics solutions."],"_banner_description":["field_612c733ed3564"],"overview_section_heading":["Course Overview of DP-750: Build Scalable Data Engineering Solutions with Azure Databricks"],"_overview_section_heading":["field_64538867ffdd0"],"after_completing_course_heading":["After completing DP-750, participants will be able to:"],"_after_completing_course_heading":["field_645c78ade3f50"],"after_completing_course":["8"],"_after_completing_course":["field_6103aae828228"],"key_features_heading":["Key Features of DP-750: Build Scalable Data Engineering Solutions with Azure Databricks"],"_key_features_heading":["field_645388ceffdd1"],"key_features":["8"],"_key_features":["field_6103aaff28229"],"who_should_attend_heading":["Who should Attend DP-750?"],"_who_should_attend_heading":["field_645388faffdd2"],"who_should_attend":["5"],"_who_should_attend":["field_6103ab0d2822a"],"prerequisites_heading":["Prerequisites of DP-750: Build Scalable Data Engineering Solutions with Azure Databricks"],"_prerequisites_heading":["field_64538a51ffdd3"],"prerequisites_text":["It is recommended that learners have: \r\n

  • Basic knowledge of data engineering concepts\r\n
  • Familiarity with SQL and Python\/Scala\r\n
  • Understanding of cloud computing (Azure preferred)\r\n
  • Basic knowledge of big data concepts and ETL processes\r\n
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\",\"answer\":\"It is designed for data engineers, big data professionals and developers working with large-scale data processing systems. \"},{\"question\":\"What is the passing score?\",\"answer\":\"Microsoft exams typically require 700 out of 1000 to pass. \"},{\"question\":\"What salary can I expect after DP-750?\",\"answer\":\"Azure Data Engineers can earn approximately \u20b912\u201330 LPA in India and $100,000\u2013$150,000 globally, depending on experience and expertise. \"},{\"question\":\"Is DP-750 difficult?\",\"answer\":\"It requires strong understanding of Spark, Databricks and data engineering concepts, making it moderately challenging. \"},{\"question\":\"What technologies are covered?\",\"answer\":\"Azure Databricks, Apache Spark, Delta Lake, Structured Streaming, Azure Data Factory and ADLS Gen2. \"},{\"question\":\"How long should I prepare?\",\"answer\":\"Typically, 4\u20136 weeks with hands-on labs and Microsoft Learn modules. \"},{\"question\":\"Is coding required? \",\"answer\":\"Yes, knowledge of Python (PySpark), SQL or Scala is essential. \"},{\"question\":\"How many days is the Instructor Led Training?\",\"answer\":\"4 Days \"},{\"question\":\"What roles can I apply for after DP-750?\",\"answer\":\"Roles include Data Engineer, Big Data Engineer, Databricks Engineer and Analytics Engineer. \"}]"],"course_files_pack":[""],"course_certificate":[""],"type":[""],"video_type":[""],"presto_player_idx":[""],"lesson_video":[""],"lesson_video_poster":[""],"lesson_video_width":[""],"lesson_shortcode":[""],"lesson_embed_ctx":[""],"lesson_youtube_url":[""],"lesson_stream_url":[""],"lesson_vimeo_url":[""],"lesson_ext_link_url":[""],"duration":[""],"preview":[""],"lesson_excerpt":[""],"lesson_files_pack":[""],"questions":[""],"quiz_style":[""],"duration_measure":[""],"correct_answer":[""],"passing_grade":[""],"re_take_cut":[""],"random_questions":[""],"answers":[""],"question_explanation":[""],"question_view_type":[""],"review_course":[""],"review_user":[""],"review_mark":[""],"order":[""],"absolute":[""],"sticky":[""],"sticky_threshold":[""],"sticky_threshold_color":[""],"stm_agenda":[""],"stm_host":[""],"stm_select_approved_denied":[""],"stm_multiselect_approved":[""],"stm_multiselect_denied":[""],"stm_date":[""],"stm_time":[""],"stm_timezone":[""],"stm_duration":[""],"stm_password":[""],"stm_waiting_room":[""],"stm_join_before_host":[""],"stm_host_join_start":[""],"stm_start_after_participants":[""],"stm_mute_participants":[""],"stm_enforce_login":[""],"stm_alternative_hosts":[""],"author_id":[""],"emails":[""],"wpdocs-meta-bdt":["29900"],"wpdocs-meta-gbp":["999"],"wpdocs-meta-rand":["7848"],"wpdocs-meta-aed":["4699"],"wpdocs-meta-usd":["1059"],"offline_price":["38870"],"offline-bdt":["38870"],"offline-gbp":["1598"],"offline-rand":[""],"offline-aed":["6199"],"offline-usd":["2199"],"_yoast_wpseo_primary_stm_lms_course_taxonomy":["62"],"_yoast_wpseo_content_score":["60"],"_yoast_wpseo_estimated-reading-time-minutes":["1"],"course_features_1_heading":["Learning objectives of DP-750: Build Scalable Data Engineering Solutions with Azure Databricks"],"_course_features_1_heading":["field_644a0fae0e67e"],"course_features_1_features_list":["6"],"_course_features_1_features_list":["field_644a0fb70e67f"],"course_features_1_background_color":["a:1:{i:0;s:5:\"white\";}"],"_course_features_1_background_color":["field_644a0fde0e681"],"after_completing_course_0_desciption":["Build and manage data pipelines using Azure Databricks. 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