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# AWS Developer

- **Company:** Compunnel Inc.
- **Location:** Raleigh, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Apache HTTP Server, Big Data, Software Quality, Databases, Continuous Integration, Data Architecture, Data Governance, Data Infrastructure, Data Vault Modeling, Data Warehousing, DevOps, Dimensional Modeling, Distributed Computing Environment, Amazon DynamoDB, Identity and Access Management, Python (Programming Language), Linux System Administration, Performance Tuning, SQL Databases, Data Streaming, Virtualization Technology, Scripting, Snowflake, Apache Spark, Cloudformation, Pyspark, AWS Data Analytics, Apache Kafka, Data Management, Functional Programming, Cloudwatch, Data Pipelines
- **Published:** September 28, 2026
- **Apply:** https://www.dice.com/job-detail/bfddb720-b268-4481-9ecb-eee07605bf92

## About the Role

5+ years of experience
Good to Have
Good to Have
AWS Solutions Architect
AWS Developer
AWS Data Analytics

Skills
SQL
Python
PySpark
AWS Cloud Services
Snowflake
dbt
Kafka
Airflow
Apache Iceberg and Lakehouse Architecture
Data Pipeline Development
Data Streaming and Distributed Data Processing
CI/CD and DevOps
Linux Administration and Scripting
Database Technologies
Networking and Virtualization Fundamentals
Data Architecture
Data Modeling
Data Governance
Requirements Gathering
Stakeholder Management
Technical Leadership
Technical Documentation
Troubleshooting and Root Cause Analysis
AI-Assisted Development
Agile Delivery
Distributed Team Collaboration

## Description

Design, develop, and support enterprise-scale data engineering solutions and scalable data pipelines
Build and optimize large-scale data processing solutions using SQL, Python, PySpark, and Spark
Develop and maintain modern data platform solutions using Snowflake, dbt, Kafka, Airflow, Iceberg, and Lakehouse architectures
Design and implement cloud-native data solutions using AWS services such as EMR, Glue, Athena, Lambda, DynamoDB, EC2, IAM, CloudFormation, and CloudWatch
Apply data architecture and modeling principles, including dimensional modeling, Data Vault, data warehousing, data governance, and master data management
Design and implement data streaming and distributed data processing solutions
Evaluate technical approaches and clearly communicate architecture decisions, implementation strategies, challenges, and outcomes
Lead technical initiatives and collaborate with engineering teams to deliver scalable data solutions
Gather business requirements and translate complex business needs into technical designs and solutions
Collaborate with business stakeholders and technical teams throughout the development lifecycle
Apply AI-assisted development tools, automation frameworks, and emerging technologies to improve engineering productivity, software quality, and delivery
Continuously evaluate and adopt modern engineering practices and technologies that improve data platform capabilities
Support CI/CD and DevOps practices for data engineering solutions
Troubleshoot performance, reliability, and data quality issues across data pipelines and platforms


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