Azure Data Engineer

Quest Global; Indianapolis (IN); On-site; USD 110,000 - 150,000; Full time

Job summary

Quest Global is seeking a data engineer in Indianapolis to implement complex data projects across multiple platforms. You will collaborate with analysts, architects and data scientists to secure the data supply chain and visualize outcomes that support informed decisions.

The role focuses on building scalable data pipelines, transforming diverse data sources into unified datasets, and ensuring data quality and security across the data lifecycle.

Qualifications

• Degree level education in Mathematics, Scientific, Computing or Engineering discipline or equivalent experience.
• 6+ years of experience in Data Engineering roles including 2+ years 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.
• Experience building, optimizing and automating data pipelines and datasets using MS Azure components.
• Proficiency in Python using different modules for data munging.
• Knowledge of data processing tech/platforms such as Spark (Databricks).
• Experience with Azure DevOps.

Responsibilities

• Working with colleagues to understand and implement data product requirements.
• Delivering the data supply chain, understanding data ingestion, transformation, and dataset creation.
• Understanding how to analyse, cleanse, join and transform data.
• Implementing designed solutions on the selected platform with Data Ops considerations.
• Ensuring cloud infrastructure can meet solution requirements.
• Planning, designing and testing implementations and correcting errors.
• Managing data security, archiving, structure and storage.
• Supporting the solution architect with data architecture deliverables.

Skills

Python

Azure DevOps

Spark / Databricks

ETL / Data integration

Education

Bachelor's degree in Mathematics, Science, Computing or Engineering

Tools

Azure SQL

ADLS

Cosmos DB

Databricks

Job description

Job Requirements

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
• 6+ 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
• 6+ 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