AWS Data Engineer

Quantum Technologies LLC; Dallas (TX); On-site; USD 77,000 - 110,000; Full time

Job summary

Quantum Technologies. LLC seeks an AWS Data Engineer to design, build, and maintain scalable data pipelines in the AWS cloud. You will collaborate with data scientists and analysts to deliver robust data solutions and optimize data ingestion, storage, and processing across data lakes and warehouses.

The role emphasizes serverless architectures, CI/CD for data platforms, and staying current with new tools and technologies. 7-month engagement in Dallas, TX with a competitive hourly rate of $68.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, MIS or equivalent
• 5 years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises
• Strong programming experience with Python, Shell scripting, and SQL
• Solid experience with AWS services: Glue, Redshift, S3, Lambda, EMR, Spark, Kinesis, and SQS; plus IAM, KMS, Secrets Manager, and Step Functions
• Experience in serverless application development and data pipeline orchestration
• Knowledge of ETL/ELT, data modeling and cloud-based data warehousing concepts
• Familiarity with data warehousing concepts and cloud-based architecture
• Strong problem-solving skills and teamwork ability
• Excellent communication and collaboration with stakeholders

Responsibilities

• Design, build, and maintain scalable data pipelines and architectures on AWS
• Create robust ingestion pipelines from on-premises to AWS and within AWS
• Develop and manage ETL/ELT processes to collect, process, and store data
• Architect end-to-end data solutions emphasizing data lakes and data warehouses
• Contribute to architecture discussions for high-scale data projects
• Perform hands-on development, unit testing, and code reviews
• Implement serverless applications using AWS Lambda, API Gateway, Step Functions
• Migrate data to AWS-based data lakes, RDS Aurora, and Redshift
• Implement high-velocity streaming with Kinesis and Kafka where applicable
• Develop and implement CI/CD strategies for data platforms
• Collaborate with cross-functional teams throughout the SDLC
• Identify and evaluate new tools and perform POCs for real-world use cases
• Monitor and optimize performance, cost, reliability, and scalability

Skills

Python

Shell scripting

SQL

AWS

Data pipelines

Education

Bachelor's degree in Computer Science / related field

Tools

Glue

Redshift

S3

Lambda

EMR

Spark

Kinesis

SQS

Kafka

CloudFormation

IAM

KMS

Secrets Manager

Step Functions

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title:AWS Data Engineer
Location: Dallas, TX
Duration: 7 Months
Bill Rate: $68/hour (C2C)
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:
We are seeking a talented AWS Data Engineer to join our dynamic Data Engineering team The ideal candidate will be responsible for designing developing and maintaining scalable data pipelines and architectures in the AWS cloud environment This role will collaborate closely with data scientists analysts and other business stakeholders to deliver robust data solutions

Key Responsibilities:

• Design build and maintain efficient reusable and reliable architecture and code for data pipelines and data applications on AWS
• Build robust data ingestion pipelines from onprem to AWS and within AWS using AWS services such as Glue Redshift S3 Lambda EMRSpark Kinesis and SQ
• Develop and manage ETLELT processes to collect process and store data from multiple sources ensuring data quality integrity and security
• Architect and implement endtoend data solutions ingestion storage integration processing access on AWS with a focus on data lakes and data warehouses
• Participate in the architecture and system design discussions for highscale data engineering projects
• Independently perform handson development unit testing and participate in code reviews to ensure adherence to best practices
• Implement serverless applications using AWS Lambda API Gateway Step Functions and other AWS technologies
• Migrate data from traditional relational databases file systems and APIs to AWSbased data lakes S3 RDS Aurora and Redshift
• Implement highvelocity streaming solutions using Amazon Kinesis SQS and Kafka preferred
• Architect and implement CICD strategies for enterprise data platforms
• Collaborate with product operations QA and crossfunctional teams throughout the software development cycle
• Stay abreast of new technology developments implement POCs for new toolstechnologies and onboard them for realworld use cases
• Identify and resolve performance issues and continuously optimize for cost reliability and scalability

Required Qualifications:

• Bachelors degree in Computer Science Software Engineering MIS or equivalent combination of education and experience
• 5 years of experience implementing and supporting data lakes data warehouses and data applications on AWS for large enterprises
• Strong programming experience with Python Shell scripting and SQL
• Solid experience with AWS services CloudFormation S3 Athena Glue EMRSpark RDS Redshift DynamoDB Lambda Step Functions IAM KMS Secrets Manager
• Experience in serverless application development and data pipeline orchestration
• Experience in system analysis design development and implementation of data ingestion pipelines in AWS
• Knowledge of ETLELT data modeling and big data technologies
• Familiarity with data warehousing concepts and cloudbased architecture
• Strong problemsolving skills and attention to detail
• Excellent communication and teamwork abilities

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.