Databricks Developer

No of Positions: 5

Location: Jaipur

Tentative Start Date: May 30, 2022

Work From : Any Location

Rate : $ 10 - 30 (Hourly)

Experience : 3 to 30 Year

Job Applicants : 12

Job Views : 425

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Job Category : Information Technology & Services

Duration : 3-6 Month

Required Skills

databricks pyspark Python azure data factory data modeling spark ecosystem ETL Azure synapse hadoop hive sqoop

Description

Overview:

As a Big Data Engineer, you will work with multiple teams to deliver solutions on the Azure Cloud using core cloud data warehouse tools (Azure Data Factory, Azure Databricks, Azure Synapse Analytics and other Big Data related technologies). In addition to building the next generation of application data platforms (not infrastructure) and/or improving recent implementations. Experience in Databricks and Spark on other cloud platforms like AWS and GCP is also relevant.

Responsibilities:

Defines, designs, develops and test software components/applications using Microsoft Azure- Databricks, ADF, ADL, Hive, Python, Databricks, SparkSql, PySpark.
Expertise in Azure Data Bricks, ADF, ADL, Hive, Python, Spark, PySpark
Strong T-SQL skills with experience in Azure SQL DW, Redshift, BigQuery
Experience handling Structured and unstructured datasets
Experience in Data Modeling and Advanced SQL techniques
Experience implementing Azure Data Factory, AWS Glue or any other data orchestration tool using latest technologies and techniques.
Good exposure in Application Development.
The candidate should work independently with minimal supervision.

Must Have:

Hands on experience with distributed computing framework like DataBricks, Hadoop, Hive, Spark-Ecosystem (Spark Core, PySpark, Spark Streaming), SparkSQL
Willing to work with product teams to best optimize product features/functions.
Experience on Batch workloads and real time streaming with high volume data frequency
Performance optimization on Spark workloads
Environment setup, user management, Authentication and cluster management on Databricks
Professional curiosity and the ability to enable yourself in new technologies and tasks.
Good understanding of SQL and a good grasp of relational and analytical database management theory and practice.

Good To Have:

Hands on experience with distributed computing framework like DataBricks, Hadoop, Hive,
Experience with Databricks migration from On-preimse to Cloud OR Cloud to Cloud
Migration of ETL workloads from Vanilla Spark implementations to Databricks
Experience on Databricks ML will be a plus
Migration from Spark 2.0 to Spark 3.0

Certifications :

Databricks Solution Architect Essentials badge
Databricks Developer Essentials
Apache Spark Programming with Databricks
Data Engineering with Databricks
Lakehouse with Delta Lake Deep Dive
Fundamentals of Unified Data Analytics with Databricks

Key Skills:

Python, SQL, Pyspark, Hive, Sqoop, YARN, Spark Ecosystem, Databricks and Azure Data Factory, Data Modelling, ETL Methodology, Azure Synapse Analytics, HDInsights, Hadoop.