Data Engineer for RR

Job Requirements

Who We Are:

Quest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries.

We are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we're eager to hear from you.

A data engineer works on implementing complex data projects with a focus on collecting, parsing, managing, analysing and visualising large sets of data to turn information into value using multiple platforms.

You will work with business analysts, architects and data scientists to understand customer business problems and needs, secure the data supply chain, implement analysis solutions and visualise outcomes that support improved decision making for a customer.

Key Accountabilities

• Working with colleagues to understand and implement data product requirements
• Delivering the data supply chain, understanding how data is ingested from different sources and combined / transformed into a single data set
• Understanding how to analyse, cleanse, join and transform data
• Implementing designed / specified solutions into the chosen platform with due consideration for Data Ops principles
• Working with colleagues to ensure that the cloud infrastructure available is capable of meeting the solution requirements
• Planning, designing and conducting tests of the implementations, correcting errors and re-testing to achieve an acceptable result
• Appreciate how to manage the data including security, archiving, structure and storage
• Support solution architect in creating architecture deliverables such as data architecture, data processing architecture, data testing strategy
  
  

Key Experience And Qualifications

• Degree level education in Mathematics, Scientific, Computing or Engineering discipline or equivalent experience
• Mandatory
• 3+ years of experience of Data Engineering roles including 2+ years in leading end-to-end design and implementation of data solutions for large scale use cases
• Experience in designing solutions using databases and data storage technology using Azure data management components - Azure SQL, ADLS, Cosmos
• Experience building, optimizing and automating data pipelines, architectures and data sets using MS Azure data management and processing components through IaaS/PaaS/SaaS implementation models implemented through custom solutions
• Proficiency in Python using different modules used for data munging
• Be up to date with data processing technology / platforms such as Spark (Databricks)
• Experienced in Azure DevOps
• Desirable
• Experience of working in tightly regulated industry is desirable
• Experience with ETL and/or data integration tool such as Informatica, Datastage, SSIS is highly desirable
• Good understanding of Azure infrastructure components and their fit in different types of data solutions
  
  

Work Experience

A data engineer works on implementing complex data projects with a focus on collecting, parsing, managing, analysing and visualising large sets of data to turn information into value using multiple platforms.

You will work with business analysts, architects and data scientists to understand customer business problems and needs, secure the data supply chain, implement analysis solutions and visualise outcomes that support improved decision making for a customer.

Key Experience And Qualifications

• Degree level education in Mathematics, Scientific, Computing or Engineering discipline or equivalent experience
• Mandatory
• 3+ years of experience of Data Engineering roles including 2+ years in leading end-to-end design and implementation of data solutions for large scale use cases
• Experience in designing solutions using databases and data storage technology using Azure data management components - Azure SQL, ADLS, Cosmos
• Experience building, optimizing and automating data pipelines, architectures and data sets using MS Azure data management and processing components through IaaS/PaaS/SaaS implementation models implemented through custom solutions
• Proficiency in Python using different modules used for data munging
• Be up to date with data processing technology / platforms such as Spark (Databricks)
• Experienced in Azure DevOps
• Desirable
• Experience of working in tightly regulated industry is desirable
• Experience with ETL and/or data integration tool such as Informatica, Datastage, SSIS is highly desirable
• Good understanding of Azure infrastructure components and their fit in different types of data solutions