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# AWS Data Engineer

- **Company:** Lightning Minds Inc.
- **Location:** Cary, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Airflow, Amazon Web Services, Amazon S3, Big Data, Cloud Engineering, Code Review, Computer Programming, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Warehousing, DevOps, Distributed Computing Environment, Python (Programming Language), Performance Tuning, Cloud Services, Workflow Management Systems, Data Processing, Cloud Platform System, Snowflake, Apache Spark, AWS Lambda, Git, Cloudformation, Data Lakes, Pyspark, AWS Glue, AWS Data Analytics, Apache Kafka, Video Streaming, Terraform, Data Pipelines, Amazon Elastic Mapreduce (EMR), Amazon Redshift, Databricks
- **Published:** June 29, 2026
- **Apply:** https://www.dice.com/job-detail/6681c4f5-9e10-4832-9163-e7e359bd485b

## About the Role

* 8+ years of Data Engineering experience.
 * 4+ years of hands-on AWS experience.
 * Strong experience with:

 * AWS Glue
 * Amazon S3
 * Amazon Redshift
 * AWS Lambda
 * Amazon EMR
 * Amazon Athena

Strong Python and PySpark programming skills.

Advanced SQL development experience.

Experience building scalable ETL/ELT pipelines.

Experience with Spark and distributed data processing.

Strong knowledge of Data Lakes and Data Warehousing.

Experience with Apache Airflow or other workflow orchestration tools.

Experience with Git, CI/CD, and DevOps practices.

Understanding of data modelling and performance optimization.

Experience working in Agile environments.

Preferred Skills

 * Financial Services or Banking domain experience.
 * Knowledge of Snowflake.
 * Experience with Kafka or streaming technologies.
 * Terraform or CloudFormation experience.
 * Databricks experience is a plus.

## Description

LPL Financial is seeking a Senior AWS Data Engineer to design, develop, and optimize scalable cloud-based data platforms and ETL pipelines using AWS services. The ideal candidate should have extensive experience in big data technologies, cloud engineering, and modern data architectures., * Design and develop cloud-native data pipelines on AWS.

 * Build and maintain ETL/ELT workflows.
 * Optimize data processing performance and scalability.
 * Integrate data from multiple enterprise sources.
 * Develop reusable data engineering frameworks.
 * Ensure data quality, security, and governance.
 * Collaborate with Architects, Data Scientists, and Business teams.
 * Troubleshoot production issues and optimize existing pipelines.
 * Participate in code reviews and mentor junior engineers.


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