Overview
Skills
Job Details
Role: Azure Data Engineer
Location: Remote (CST/EST)
Type: 12 month contract
Requirement Description:
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5+ years of experience in an Enterprise Data Management or Data Engineering role
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3+ of hands on experience in building metadata driven data pipelines using
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Azure Data Factory, Databricks / Spark for Cloud Data Lake
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5+ years hands on experience with using one or more of the following for data analysis and
wrangling Databricks, Python / PySpark, Jupyter Notebooks
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Expert level SQL knowledge on databases such as but not limited to Snowflake, Netezza,
Oracle, Sql Server, MySQL, Teradata
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3+ years of hands on experience on one or more of big data technologies such as Cloudera
Hadoop, Pivotal, Vertica, MapR is a plus
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Experience working in a multi developer environment and hands on experience in using either
azure devops or gitlab
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Preferably experienced in SLA driven Production Data Pipeline or Quality support
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Experience or strong understanding of the traditional enterprise ETL platforms such as IBM
Datastage,Informatica, Pentaho, Ab Initio etc.
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Functional knowledge of some of the following technologies - Terraform,Azure CLI, PowerShell,
Containerization (Kubernetes, Docker)
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Functional knowledge of one or more Reporting tools such as PowerBI, Tableau, OBIEE
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Team player with excellent communication skills, ability to communicate with the customer
directly and able to explain the status of the deliverables in scrum calls
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Ability to implement Agile methodologies and work in an Agile DevOps environment
Qualifications:
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Bachelors degree in Computer Science or Engineering or Mathematics or related field and 5+
years of experience in various cloud technologies within a large-scale organization
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Personal Attributes: Self-starter, Collaborative, Curious, Strong work ethic, highly motivated,
Team oriented
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Experience designing and building complex data pipelines in an agile environment
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Expertise on data analysis and wrangling using sql, python, databricks
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Experience with modern cloud development and design concepts; software development
lifecycle; multi-developer code versioning and conflict resolution; planning, design, and
problem resolution enterprise data applications / solutions