Data Engineer

CONSORTIUM
United States
25 days ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

JavaScript (Programming Language) Agile Methodology Artificial Intelligence Amazon Web Services Amazon S3 Automation of Tests Unit Testing Cloud Computing Extract Transform Load (ETL) Data Mining Data Warehousing DevOps
+25 more
Amazon DynamoDB ECMAScript Event-Driven Programming Python (Programming Language) Node.Js Power BI Amazon Simple Notification Service (SNS) Software Deployment Software Engineering SQL Databases Systems Integration Tableau (Software) Freeform SQL Data Ingestion AWS Lambda Cloudformation Production Code Data Analytics Functional Programming Amazon Simple Queue Service (SQS) Stream Analytics Looker Analytics Serverless Computing Amazon Redshift Microservices

Job description

Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies

Builds, tests, deploys and maintains production code for complex transactional applications using event driven microservices, node.js, Python languages. Incorporates Cloud technologies on new application development to include micro-services, SQL and AWS services such as lambda, S3, SQS, SNS, DynamoDB, Quicksight, AWS Redshift, Opensearch.

Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance

Requirements

Team: Team is Intel delivery platform and Cumulus - lots of data exchanges: AWS platform using Redshift as data warehouse - Dynamo of meta-data. They are working on evolving code for digital products and need a dynamic Senior Data engineer who will also design, build and write test automation.

Profile: Senior Data Engineer with SME in data analytics end AI work within our tech stack; 5+ years of experience. TECHNICAL SKILLS

Must Have

  • AWS - CloudFormation
  • AWS - Dynamo
  • AWS - Lambda
  • AWS - S3
  • AWS - SNS/SQS
  • AWS Step Function
  • BI Tool
  • Gen AI
  • Node.js Development
  • Python
  • RedShift/SQL

Tech Stack Grid

RedShift/SQL

BI Tool

AWS - Dynamo

Gen AI

AWS Step Function

AWS - Lambda

AWS - S3

AWS - SNS/SQS

AWS - CloudFormation

Python

node.js Development

JavaScript (ES6)

Data Engineer must be a skilled engineer with an unwavering passion for excellence in Software Engineering and drive to transform that passion into consistent excellence in product development. The candidate must be customer-obsessed, have strong analytical and communication skills, enjoy working with native AWS services, and thrive on solving challenging business problems. The candidate will partner with Product Owners/Architects, Developers, and other Software Engineers to help design, define, implement functional features, system level validation and verify features of product development. Qualified candidates will show an aptitude learning and implementation of advanced software engineering practices in Data Analytics, AWS, Microservices environment to solve complex problems with a mission to release high quality software that is resilient and optimally performing. Candidates will be engaged in both data and analytics reports development and quality engineering, testing and automation as a data engineer., Expert in writing and optimizing complex SQL queries for data extraction, transformation, and reporting (e.g., SELECT, JOIN, GROUP BY, HAVING, WINDOW functions). Expert integrating Redshift Serverless with AWS services such as S3, Glue, Lambda, Athena, and Kinesis BI tools like Tableau, Quicksight, or Looker for real-time analytics and dashboards Expert in building serverless ETL pipelines with Lambda to automate data ingestion and transformation into Redshift. Experience in integrating Redshift Serverless with Experience of NodeJS and Python Working knowledge of any AI technologies Experience in working with AWS services, deploying applications to AWS Exposure to DevOps tools and automation Effective communication skills are a must along with a strong customer service orientation, and the ability to clearly discern client needs.

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