Position: BI/Reporting Engineer : What we're looking for:
Overall 10 years of experience in Industry including 6+Years of experience as developer using Databricks/Spark Ecosystems.
Hands on experience on Unified Data Analytics with Databricks, Databricks Workspace User Interface, Managing Databricks Notebooks, Delta Lake with Python, Delta Lake with Spark SQL.
Good understanding of Spark Architecture with Databricks, Structured Streaming. Setting Microsoft Azure with Databricks, Databricks Workspace for Business Analytics, Manage Clusters In Databricks, Managing the Machine Learning Lifecycle
Hands on experience Data extraction(extract, Schemas, corrupt record handling and parallelized code), transformations and loads (user - defined functions, join optimizations) and Production (optimize and automate Extract, Transform and Load)
TECHNICAL SKILLS
Spark Data Frame API
Python for Data Science
Spark Programming
SQL for Data Analysis
Simplify Data analysis With Python
Manage Clusters Databricks
Databrick Administration
Data Extraction and Transformation and Load
Implementing Partitioning and Programming with MapReduce
Setting up Azure Databricks Account
Linux Command
What you'll be doing:
Experience in developing Spark applications using Spark-SQL in Databricks for data extraction, transformation, and aggregation from multiple file formats for Analyzing & transforming the data to uncover insights into the customer usage patterns.
Extract Transform and Load data from sources Systems to Azure Data Storage services using a combination of Azure Data factory, T-SQL, Spark SQL, and U-SQL Azure Data Lake Analytics. Data ingestion to one or more Azure services (Azure Data Lake, Azure Storage, Azure SQL, Azure DW) and processing the data in Azure Databricks
Develop Spark applications using pyspark and spark SQL for data extraction, transformation, and aggregation from multiple file formats for analyzing and transforming the data uncover insight into the customer usage patterns
Hands on experience on developing SQL Scripts for automation
Responsible for estimating the cluster size, monitoring, and troubleshooting of the Spark databricks cluster
Ability to apply the spark DataFrame API to complete Data manipulation within spark session
Good understanding of Spark Architecture including spark core, spark SQL, DataFrame, Spark streaming, Driver Node, Worker Node, Stages, Executors and Tasks, Deployment modes, the Execution hierarchy, fault tolerance, and collection
Collaborate with delivery leadership to deliver projects on time adhering to the quality standards
Contribute to the growth of the Microsoft Azure practice by helping with solutioning for prospects
Problem-solving skills along with good interpersonal & communication skills
Self-starter who can pick up any other relevant Azure Services in the Analytics space
Location: IN-KA-Bangalore, India (SKAV Seethalakshmi) GESC Time Type: Full time Job Category: Information Technology
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