Azure Databricks Courses near me in Bangalore, India

I'm an Azure Data Engineer offering 10+ years of teaching experience and 6+ years IT experience in data engineering, data warehousing, machine learning, and business intelligence realm. I have completed my engineering (B.Tech) from NIT RAIPUR. -All Classes with Lab sessions and Daily Practice. -End to End Project Implementation using Azure. -Trained people in becoming Microsoft certified cloud developer from scratch. -Get online recording of classes with lifetime access. -Helped experienced IT people to secure good job in Azure cloud technology. -Providing support in interview preparation and Resume Building. -Support for fresher's to secure good jobs as Business Analyst, Data Analyst, Data Engineer in 2-3 Month of Training -Helped people to move from SSIS, SSRS, SSAS to Azure Cloud Enviornment. -Providing Microsoft CertificationTraining and Support. -Practice is key to success. -I believe in Practical Implementation instead of theoretical knowledge.

Objectives – Having 18.5 years of experience As a Technical Lead and Architect, I am passionate about leveraging my expertise in Databricks, Data Build Tool, Spark, Confluent Kafka, Data Lake, Lake House and Cloud Solutions to drive innovation and efficiency. With a solid background in data architecture and IT Infrastructure, I am to contribute to the robust and vision of your company by providing ro bust technical solutions that align with strategic business goals. My Goal is to enhance data-driven decision-making processes, optimize big data pipelines and implement secure and scalable cloud architectures that people the organization forward in the ever-evolving technical landscape. Certification & Achievements – 1. Confluent Certified Administrator for Apache Kafka: expiry July 2026. Confluent Certified Administrator for Apache Kafka • Amit Raj • Confluent 2. Databricks Certified Data Engineer Professional: expiry Aug 2026 Databricks Certified Data Engineer Professional • Amit Raj • Databricks Badges 3. Databricks Accredited Lakehouse Fundamentals: expiry June 2025 Academy Accreditation - Databricks Lakehouse Fundamentals • Amit Raj • Databricks Badges 4. Microsoft Certified: Azure Administrator Associate (AZ104): Microsoft certification ID: 1100039942 Expires on: August 3, 2025 Credentials - AmitRaj-8869 | Microsoft Learn 5. Microsoft Certified: Azure Security Engineer Associate (AZ500): Microsoft certification ID: 1100039942 Expires on: August 6, 2025 Credentials - AmitRaj-8869 | Microsoft Learn 6. Recognition certificate from Fidelity for designing global solutions for Data exchange. 7. Got Achievement medal from DIB(Client) with appreciation for design event-based enterprise architecture & contribution – EventHub SUMMARY • Overall total of 18.5+ years of Experience years of Experience in Application Design, Development & Deployment of Hadoop Eco System/Java/J2EE systems with good exposure to Enterprise Architecture. • Relevant Experience 9.2 years in Big Data technologies working with multiple clients and domain knowledge. • Experienced in Cassandra data modelling, cluster setup and data management. • Experienced in working with Spark-SQL, Spark SQL and Spark Structure Streaming, MLib to process and analyse data queries. • Experienced in designing solutions using Spark Streaming and Kafka Streaming for Payment Gateway/point of sales events. • Individual Contribution (Kafka Architect): Delivered UAT and PROD Cluster within the timeline for Kafka cluster using Cloudera 6.x, CSP 2.0. • Implemented a unified data platform to gather data from different sources using Kafka Producers and consumers in Scala and java. • Solid background in Object-Oriented analysis & design, UML and various design patterns. • Worked using Azure cloud(Blob, EventHub), Kubernetes, docker with Spark, scala, Schema Registry, Avro Schema with home security application for Honeywell • Implemented KSQL, KTable and KStream using Confluent Kafka along with Kafka Connect. • Hands-on Data bricks - Databricks Clusters, Data Lakehouse, Delta lake, DBFS, EXPLORE, Analyze, Clean, Transform and Load Data using Databricks. • Experience with Azure: Azure Synapse Analytics, ADLS, ADF, CosmoDB, Azure Function, Stream Analytics, Power BI. • Experience with SQL and NoSQL databases including Mysql, Oracle, Cassandra, and PostgreSQL. BigTable • Experience building and optimizing the ‘big data’ data pipeline. • Experince with Azure Devops, CI/CD pipeline, Kubernetes and docker • Motivated Technical Architect with 5 years of progressive experience. • Having Experience AWS (Ec2,S3) • Having experience with Snowflake to design data lake and load data from multiple sources to the Snowflake database. • Effectively manages assignments and team members. • Dedicated to self-development to provide expectation-exceeding service. Customer-focused, successfully contributing to company profits by improving team efficiency and productivity. • Utilizes excellent organizational skills to enhance efficiency and lead teams to achieve outstanding delivery. SKILLS == ===================  Database architecture  Database architecture development  Data Architecture  Big Data ETL  Technical solution development  Azure data solutions  Data insight provision  Technical guidance  IT Architecture  Technical solutions  Big data frameworks Technical Skills: Hortonworks2.5, Cloudera5/6, Apache Hadoop2/3 ,Spark2/3,Apache Kafka, Confluent Kafka, Hive 2/3, Impala, Sqoop, OOZie, Zookeeper, Snowflake, Data Build tool (DBT), HBase, Apache Cassandra /DataStax Cassandra, Data Bricks, Azure Cloud, AWS cloud, Talend, Airflow etc. Programming Language Python , Scala & Java Other Tools Kibana, Logstash, ElasticSearch, ELK. ============================= PROJECT UNDERTAKEN: Project: Implementation of Data Warehouse and reporting platform Roles: Databricks Architect & Engineer Teams: 12 members Technical Skills: Azure Cloud, Azure Data Factory (ADF), ADLS, Databricks, Spark3.x, Python, Scala2.15, DB2, Oracle 12g, Azure SQL My Contribution Data Bricks Infrastructure Solution: - Configured Unified Data Access Control using Unity Catalog – E1 & BY System provide a specific set of permissions, like Read Only, or, Write Only to a specific Group of Users on one, or, some of the Delta Tables, or, even at the Row Level, or, Column Level, which can contain Personally Identifiable Information, i.e., PII, of that Delta Tables - Provide Data Governance with centralized place: administer (TAI) the access to the data, and, also audit the access to the data. - Applied Data lineage for E1 & BY tables with look-up tables using Unity Catalog. - Implemented Data sharing protocol to apply secure data sharing downstream using Unity Catalog and - Design Architecture of Unity Catalog which can be linked to multiple Databricks Workspaces- DEV, UAT, PROD environment. - Created Metastore for the Unity Catalog - Apply User Management of the Unity Catalog for the TAI Lakehouse project: Users, Groups, or, the Service Principle, and, the permissions those have - Configure Data Bricks Cluste with spark 3.x for DEV, UAT & PROD for TAI -E1 & BY System. - Design & apply medallion architecture, Setup a Data Lake house with Bronze, Silver and Gold layers of a storage system using Azure Data Lake Gen2. Azure Cloud Infra and Security: - Install self-hosted integration runtime for the DB2 ON DEV, UAT & PROD and Oracle on-prem cluster on the source system. - Install Azure Virtual network managed IR On DEV, UAT & PROD. - Installed Db2 connector on DEV, UAT & PROD. - Created linked service lnk_BY_Azure_SQL, lnk_E1_Azure_SQL, lnk_Db2_E1 - Install and Configure Azure Key-Vault, added all the credential for Azure SQL, ADLS, Databricks, Users, global users, linked service to Azure Key Vault. – DEV, UAT & PROD. - Created 3 nodes for DEV and 5 nodes for PROD cluster to migrate data. - Setup and configure Azure Active Directory to provide team access policy for Databricks cluster, Azure Data Factory, Azure SQL, Azure Data Lake house. - Coordinate with TAI Client and Microsoft support team to resolve throughput issues. As Azure & Databricks Data Engineer: - developed most critical data ingestion pipelines using Azure Data Factory (ADF) for E1 to migrate 12.8TB of 120 tables from Db2 to ADLS RAW as a parquet file. There are many large tables with 2-4 TB of volume data containing 400 to 800 million records. - Initial & Incremental migration pipelines for both the E1 and BY sources with a watermark based on Julian's date & time - Design Audit table (Process log) and Control table (System) to achieve dynamic pipeline and audit information for master and child pipeline. - Design architecture solution to achieve delete for PKSNAPSHOT – E1 & BY. - Build dynamic delete pipeline using ADF (load PKTBL), Databricks PySpark for Daily, Weekly, OnDemand, and Yearly frequency to delete records from target (Analytics layer – gold layer) based on source system delete column and delete table - Build transformation using Datarbicks Spark with Scala for E1 to - Apply a transformation with a lookup table and transform to the Silver layer. - Build transformation to transform on Analytics layer (Gold) using Databricks Spark & scala. - Implemented UPSERT using Spark Structure Streaming with 5 minutes on the Analytics layer - Design pipeline architecture for master pipeline, child pipeline with different activity ID, Pipeline ID, Master pipeline ID with different pipeline Run ID to make sure for smooth transition audit. - Build logic, developed using Pyspark on Datarbicks – applied on DEV, UAT & PROD to check counter – master pipeline IN PROGRESS - or NOT so that pipeline execution should not overlap. - Pass pipeline parameter to insert or update Audit/Control table using Databricks -Pyspark. - Monitor Performance in DEV & PROD, worked with the team to reduce time. - Milestone – to achieve 10-minute SLA for Incremental load on E1 & BY (end-to-end completion time) - Milestone – achieved 1.53.45hrs to load (400millions record with2.3TB) at RAW as parquet file using ADF pipeline - Interact with Azure Devos’s engineer to build a CICD pipeline for DEV, UAT & PROD with - Develop pipeline as POC using Databricks Workflow, compare the cost with Azure Pipeline, and present to the client. My Contribution to Past Project: Project: Data Exchange (Security Framework) Roles: Technical Lead & Architect – Confluent KStream & KSQL Client: Fidelity & Westpac Team: 9 members Technical Skills: AzureDevops, Jdk 19.0, Confluent Kafka, Kstream, KSQL, Azure Databricks, DBFS, Delta lake, Azure Data Factory, ADLSGen2, Confluent Schema Registry, AES Algorithm, Hash Algorithm, Kubernetes Cluster(AKS).

I teach Big Data ETL Testing, Microsoft Azure, Azure Databricks, and related Big Data technologies. With over 23 years of industry experience and 7 years of active training, I focus on helping students and working professionals gain practical, hands-on skills that are directly applicable to real-world projects. My aim is to make complex technologies accessible, understandable, and usable in professional environments. I hold a Master of Science (M.S.) degree in Software Systems, which has provided me with a strong theoretical foundation. Over the years, my industry experience has spanned multiple domains and geographies, allowing me to understand the challenges professionals face and how to effectively prepare students for them. Throughout my career, I have worked on a wide range of projects across Big Data, Cloud, and Analytics technologies. This exposure has enabled me to incorporate real-life use cases and practical examples into my teaching, helping learners not just understand concepts but confidently apply them in professional scenarios. My teaching methodology is structured, interactive, and practical. Each session is planned with a clear lesson structure, ensuring that students gain both conceptual clarity and hands-on expertise. I emphasize problem-solving, live demonstrations, and exercises that replicate real-world situations to prepare learners for industry demands. I conduct classes both online and offline, using PPTs and whiteboards to enhance understanding and visualization of complex concepts. My sessions are designed to engage students actively, encourage questions, and provide detailed step-by-step guidance to ensure everyone progresses effectively. I provide comprehensive conceptual notes, hands-on demonstrations, and assignments to reinforce learning. Additionally, I upload session videos on YouTube, enabling students to revise and revisit topics at their own pace, which helps in mastering the material thoroughly. My ultimate goal is to empower students with skills that are immediately applicable in their careers. I aim to create a learning environment where technical knowledge, practical experience, and problem-solving capabilities come together, helping learners succeed in both academic and professional pursuits.

I have 5+ years of professional experience in Azure Data Engineering, with strong hands-on expertise in Azure Databricks, PySpark, and big data processing. I provide industry-oriented training in Azure Databricks, focusing on practical implementation and real-time data engineering use cases. My training is designed to help learners understand end-to-end big data processing using Azure Databricks and Apache Spark, starting from fundamentals to advanced optimization techniques. The key topics covered in my Azure Databricks training include: Introduction to Azure Databricks Databricks workspace overview Cluster creation and management Notebooks and collaborative development Apache Spark Architecture Spark components (Driver, Executor, Cluster Manager) RDD vs DataFrames vs Datasets Distributed data processing concepts Working with DataFrames Creating DataFrames Data transformations Reading data from Azure Blob Storage to Databricks Reading Data from Azure Data Lake Storage (ADLS Gen2) Mounting storage Accessing files from ADLS Gen2 Data ingestion best practices PySpark Functions and Joins Built-in PySpark functions Filtering, aggregations, and transformations Different types of joins (Inner, Left, Right, Full) Slowly Changing Dimension – SCD Type 2 Concept and real-time use cases Implementing SCD Type 2 using PySpark and Delta Lake Delta Lake vs Parquet Differences and advantages ACID transactions Data versioning and time travel Databricks Optimization Techniques Partitioning Caching File compaction Query performance tuning Auto Loader Incremental data ingestion Handling streaming data Schema evolution Delta Live Tables (DLT) Data pipeline automation Data quality checks Pipeline monitoring Workflows in Databricks Job scheduling Workflow orchestration Automation of data pipelines The training includes hands-on labs, real-time scenarios, and project implementation, where learners build complete data pipelines using Azure Databricks integrated with Azure Data Lake and Azure Data Factory. I also provide: Practical assignments and coding exercises Real-time project guidance Azure Data Engineer interview preparation Best practices followed in industry projects My objective is to help learners gain strong practical expertise in Azure Databricks and PySpark, enabling them to work confidently on real-time big data and data engineering projects.

I have 10+ Years of experience On Azure Data Engineering(Azure Data Factory,Databricks,pyspark) with Real time scenarios and Real time projects. 100% Placement Guarntee Programm running. Every student placing with 300% hike and most of students getting offers with 20 Lakhs pacakge and more than that with relavant 3 years on Data Engineer role Placing Every student on Permanent Work From Home Job Opportunities

I'm a Product Owner with 9 years of experience and counting. Working with Diageo currently one of the biggest Liquor manufacturing companies in the world. I have experience in SQL, Python, PowerBi, other Microsoft Applications, Databricks, Azure Dev Ops. Anything that you need on how to navigate your professional career, I have the knowledge and skillset that can help you get a head start.

I have 15 years of experience in DevOps and cloud technologies including git, GitHub, Docker, Kubernetes, terraform, Azure DevOps pipelines, promotes, grafana, Jenkins, helm charts and ArgoCD, Data Science, Machine Learning, and Artificial intelligence.

I have 14 years of IT industry experience. Overall 5 + years in Azure Databricks, ADF, SQL. I am having BE degree from VTU. I would love to train student with real time live project experience of multiple Azure Databricks to land in their dream job opportunities.

I am a technology enthusiasts and working in big data domain for the last 6 years. My key skills include python, spark, snowflake, big data tech stack.

I am Solution Architect working on Dual Cloud - AWS and Azure. We have Data lake on AWS and Azure and use Databricks a lot.

Having 14 years of experience in Data Engineering and Architecture and 5 years experience in databricks product. 4 years of experience in giving training in databricks and informatica power center

From Simplilearn and Tech Head 💎 About Dr T (Tej) Dr T is a self-made millionaire, visionary technologist, and strategic force behind global digital transformation. As a Grand Master of 5 critical technologies—AI, Big Data, Data Science, Full Stack Development, and Cloud—he has built frameworks that power enterprise-grade systems across OpenStack, IBM, Azure, AWS, and GCP. With over 5 certifications in AWS, 6 in Azure, and 4 in Snowflake, he stands as one of the highest-certified Principal Data Scientists in the ecosystem. A silent executor, Dr T has consistently delivered outcomes that shift organizational direction—often without fanfare, but always with unmatched precision. Featured across elite stages like AWS re:Invent, Dr T is not just a technologist—he’s a movement for resilience, intelligence, and purpose-led innovation. Whether it's solving billion-row data problems or mentoring the next generation, Dr T leads with integrity, mastery, and a legacy mindset.

I can teach every topic very easily and make it stronger for the students.

Welcome to our institute, where we specialize in cutting-edge training programs such as Azure Data Factory, Azure Databricks, ETL, ETL Testing, and Snowflake. Established just 6 months ago, our commitment is to provide high-quality education in the rapidly evolving field of data management. Our team comprises four dedicated trainers, each bringing a wealth of experience with 8 to 14 years in the industry. All our trainers are graduates, ensuring a strong foundation in their respective fields. In our pursuit of excellence, we provide certifications upon course completion, empowering our students with recognized credentials in the domain. Our courses are conducted online, offering the flexibility to learners to access our programs from the comfort of their own space. What sets us apart is our emphasis on real-time training and interactive classes. We believe in practical, hands-on learning, ensuring that our students are well-prepared for the challenges they may face in the professional arena. Our use of PowerPoint presentations and videos enhances the learning experience, providing a visual and engaging component to our training sessions. Join us in this dynamic learning environment where we bring together expertise, experience, and state-of-the-art training methods to empower you in the realm of data management. Let's embark on this journey of knowledge together, unlocking the potential of data in the digital age!