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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AWS Data Engineer - **Company:** Visionary Innovative Technology Solutions LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Cloud Computing Security, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Cursor (Graphical User Interface Elements), Database Queries, Database Theory, Elasticsearch, Identity and Access Management, Python (Programming Language), Machine Learning, NumPy, SQL Databases, Systems Integration, Unstructured Data, Data Processing, Data Ingestion, Sql Optimization, GitHub Copilot, Large Language Models, Prompt Engineering, Apache Spark, Generative AI, Git, Pandas, Data Lakes, Pyspark, Scikit Learn, AWS Data Analytics, Data Pipelines - **Published:** August 5, 2026 - **Apply:** https://www.dice.com/job-detail/801fc2a1-9653-4afb-b133-86a1f3ea5b6f ## About the Role * 14+ years of overall IT experience with strong Data Engineering background. * Extensive hands-on experience with AWS Data Engineering. * Strong Python programming skills. * Advanced SQL skills including complex queries, CTEs, window functions, and optimization. * Strong experience with AWS S3, Glue, Redshift, Lambda, EMR, and Athena. * Strong experience designing ETL/ELT pipelines. * Hands-on experience with PySpark / Apache Spark. * Experience with data lake and data warehouse architecture. * Experience with Airflow / AWS MWAA. * Strong understanding of data modeling and database concepts. * Experience with Git and CI/CD. * Strong understanding of cloud security, IAM, encryption, and AWS best practices. AI/GenAI Skills - Preferred * Generative AI / LLM experience. * Amazon Bedrock. * RAG architecture. * Prompt Engineering. * Embeddings and Vector Databases. * LangChain / LlamaIndex. * OpenAI / Azure OpenAI / Anthropic. * Pinecone / OpenSearch / Elasticsearch / FAISS. * Machine Learning and model integration. * AI/ML API integration. ## Description * Design and develop scalable data pipelines and data engineering solutions on AWS. * Build and maintain robust ETL/ELT pipelines using Python and AWS services. * Develop data ingestion, transformation, validation, and processing frameworks. * Design and implement enterprise AWS Data Lake and Data Warehouse architectures. * Work with AWS services such as S3, Glue, Lambda, EMR, Redshift, Athena, Kinesis, Step Functions, and ECS/EKS. * Develop complex data processing solutions using Python, PySpark, and SQL. * Design data models for structured, semi-structured, and unstructured datasets. * Optimize data pipelines for performance, scalability, reliability, and cost. * Implement data quality, governance, lineage, validation, and monitoring processes. * Develop orchestration workflows using Apache Airflow / AWS MWAA. * Build CI/CD pipelines for data engineering applications and infrastructure. * Collaborate with architects, data scientists, ML engineers, application developers, and business stakeholders., * Build data pipelines supporting Machine Learning and Generative AI use cases. * Prepare, clean, transform, and engineer datasets for AI/ML models. * Work with LLMs, embeddings, vector databases, and RAG pipelines. * Experience with Amazon Bedrock and foundation models is highly desirable. * Develop AI-enabled data processing and automation solutions. * Integrate pre-trained AI/ML models through APIs. * Support model training, evaluation, deployment, and monitoring workflows. * Use Python, Pandas, NumPy, Scikit-learn, and other AI/ML libraries as needed. * Work with AI coding assistants such as GitHub Copilot, Amazon Q Developer, or Cursor. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Vectorize all the things! 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