Enterprise Analytics Data Engineer

Enterprise Analytics Data Engineer

  

This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know diverse backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

   

 

HPE Global IT is a dynamic organization enabling the enterprise to innovate and lead the industry with our consumption-based IT transformation and our consulting, financial, educational, and operational support services.  Join us as we develop innovative solutions that revolutionize how we help customers by simplifying their operations and move the world forward. Join us and redefine what’s next for you

Job Family Definition:

Researches, designs, develops, configures, integrates, tests and maintains existing and new business applications and/or information systems solutions including databases through integration of technical and business requirements. Applications and infrastructure solutions include both 3rd party software and internally developed applications and infrastructure. Responsibilities include, but are not limited to, analysis of business requirements, coding of modifications or new program, creation of documentation, testing and maintenance of applications, infrastructure, and information systems including database management systems. Works within the Information Technology function, obtaining resources and working in support of objectives and strategies. Provides required documentation and participates in architecture reviews to ensure that the solutions comply with standards and use approved technologies. Typical customers are company end users and various functional areas such as Supply Chain, Research and Development, Marketing, Finance, a business, or the company.

Management Level Definition:

Contributions include applying developed subject matter expertise to solve common and sometimes complex technical problems and recommending alternatives where necessary. Might act as project lead and provide assistance to lower level professionals. Exercises independent judgment and consults with others to determine best method for accomplishing work and achieving objectives.

What you’ll do:

Responsibilities:

• Participates as a member of data development team or cross functional teams; and may lead a project/ program development team; Performs analysis of functional and business requirements.

  •    Completes data analysis, and develops batch, real-time, and real time streaming data integration codes to implement solutions.

  •    Develops data transformation codes across data lake layers independently.

  •    Participates in code reviews and may lead code reviews.

  •    Works with business and system teams to design, prepare and automate test cases.

  •    Applies in-depth or broad technical knowledge to maintain data engineering. Performs solution design. Applies the company, open source, and 3rd party technologies to highly complex infrastructure and software solutions.  Knowledge and Skills:

• 3+ or more years of experience in exploratory data analysis and integration

  •    3+ or more years of experience writing SQL, and at least one programming language including Python, Scala, Spark

• •   Should have worked in real time Big Data Projects with hard core knowledge about Hadoop and Spark/Scala programming.

  •    Knowledge of workflow tools such as Oozie, and Airflow

  •    Proficiency in big data technologies including Hive, Spark, Scala, and No SQL

  •    Knowledge of data structures, algorithms

  •    Root cause analysis, identifying opportunities for continuous improvement.

  •    Experience of multiple full release cycles.

  •    Understanding of Software Test methodologie