Azure Data Engineer

A Chemical & Purifier Company headquartered in the US.

Azure Data Engineer

Azure Data Engineer at A Chemical & Purifier Company headquartered in the US. · Bengaluru (Bangalore) · 4 - 9 years · ₹15L - ₹18L / yr · Posted 13 May 2021

Azure Data Engineer

at A Chemical & Purifier Company headquartered in the US.

Agency job

via Multi Recruit

4 - 9 yrs

₹15L - ₹18L / yr

Bengaluru (Bangalore)

Skills

Azure data factory

Azure Data factory

Azure Data Engineer

SQL

SQL Azure

ADF

azure

Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
Author data services using a variety of programming languages
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Keep our data separated and secure across national boundaries through multiple data centres and Azure regions.
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.
Work in an Agile environment with Scrum teams.
Ensure data quality and help in achieving data governance.

Basic Qualifications

2+ years of experience in a Data Engineer role
Undergraduate degree required (Graduate degree preferred) in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
Experience using the following software/tools:
Experience with big data tools: Hadoop, Spark, Kafka, etc.
Experience with relational SQL and NoSQL databases
Experience with data pipeline and workflow management tools
Experience with Azure cloud services: ADLS, ADF, ADLA, AAS
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets
Strong analytic skills related to working with unstructured datasets
Build processes supporting data transformation, data structures, metadata, dependency, and workload management
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
Experience supporting and working with cross-functional teams in a dynamic environment

Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
Author data services using a variety of programming languages
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Keep our data separated and secure across national boundaries through multiple data centres and Azure regions.
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.
Work in an Agile environment with Scrum teams.
Ensure data quality and help in achieving data governance.

Basic Qualifications

2+ years of experience in a Data Engineer role
Undergraduate degree required (Graduate degree preferred) in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
Experience using the following software/tools:
Experience with big data tools: Hadoop, Spark, Kafka, etc.
Experience with relational SQL and NoSQL databases
Experience with data pipeline and workflow management tools
Experience with Azure cloud services: ADLS, ADF, ADLA, AAS
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets
Strong analytic skills related to working with unstructured datasets
Build processes supporting data transformation, data structures, metadata, dependency, and workload management
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
Experience supporting and working with cross-functional teams in a dynamic environment

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