Azure Data Engineerly - Shift Work for US client

Azure Data Engineerly - Shift Work for US client

We are actively seeking a highly motivated and committed Data Engineer with significant expertise in the Azure Cloud Platform to become a valuable member of our team. This role involves working with our esteemed US client and adhering to a shift schedule of 2pm to 10pm VNT. Preference will be given to candidates who possess either the MS Azure certification (DP 203) or the Databricks Data Engineering Certification.
JOB DESCRIPTION
•Collaborate with customer to gather requirements and to understand their business processes.
•Create and maintain optimal data pipeline architecture,
•Assemble large, complex data sets that meetfunctional / non-functional business requirements.
•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 usingSpark,SQL andAzure‘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.
•Use tools to deploy and monitor the performance of the systems in production.
REQUIREMENTS
•Demonstrate knowledge and real-world experience onBig data technologies. A successful history
of manipulating, processing and extracting value from large datasets.
•Advanced working SQL knowledge and experience working with relational databases, query
authoring (SQL) as well as working familiarity with a variety of databases.
•Strong analytic skills related to working with unstructured datasets.
•Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
•We are looking for a candidate with>3+ years of experience in a Data Engineer role.They
should also have experience using the following software/tools:
oExperience with big data tools: Hadoop, Spark, Kafka, etc.
oExperience with relational SQLdatabases such as Oracle, SQL Server, MySQL or
Postgres.
oExperience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow,
etc.
oExperience with stream-processing systems: Storm, Spark-Streaming, etc.
oExperience with object-oriented/object function scripting languages: Python, Java, C++,
Scala, etc.
•For senior data engineers also shouldhave demonstrable experience in
Project management and organizational skills.

About Rackspace Technology
We are the multicloud solutions experts. We combine our expertise with the world’s leading technologies — across applications, data and security — to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world-class talent. Join us on our mission to embrace technology, empower customers and deliver the future.
 
 
More on Rackspace Technology
Though we’re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.
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