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# Data Engineer

- **Company:** PERIGONSOFT LLC
- **Location:** Columbia, MD, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Microsoft Azure, Cloud Database, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Systems, DevOps, Github, Python (Programming Language), Performance Tuning, Software Tools, Scala (Programming Language), SQL Databases, Data Streaming, Systems Integration, Azure Data Factory, Large Language Models, Snowflake, Prompt Engineering, Apache Spark, Event Driven Architecture, Pyspark, Infrastructure Automation Frameworks, Information Technology, Apache Kafka, Data Management, Terraform, Data Pipelines, Serverless Computing, Key Vault, Databricks
- **Published:** September 29, 2026
- **Apply:** https://www.dice.com/job-detail/e6865896-ce5e-4f98-b270-43c46d3240a3

## About the Role

* 8+ years of experience in Data Engineering
 * Data Engineering: Databricks, Spark (PySpark), Python/Scala, SQL, Snowflake
 * Azure: Azure Cloud Services, ADF, ADLS, Azure Functions, Key Vault, DevOps
 * AI/GenAI: LLM Fine-Tuning, RAG, Prompt Engineering
 * Automation & DevOps: Airflow, GitHub, GitHub Actions, CI/CD, Terraform, Infrastructure Automation
 * Kafka, Event-Driven Architecture, CDC/Streaming Integrations

Preferred Qualifications:

 * Bachelor's or Master's degree in Computer Science, Engineering, or related field
 * Azure certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect) is a plus
 * Experience working in large-scale enterprise or regulated industry environments (finance, healthcare, insurance)
 * Strong communication skills with ability to work directly with client stakeholders

## Description

We are looking for an experienced Data Engineer with 9+ years of experience to design, build, and maintain data pipelines using Databricks, Spark, and Azure cloud services. The ideal candidate has hands-on experience with modern data engineering tools, cloud automation, and event-driven architectures., * Design, develop, and optimize scalable data pipelines using Databricks and Spark (PySpark)

 * Build and maintain ETL/ELT workflows integrating with Snowflake and other data platforms
 * Develop and manage Azure-based data solutions using ADF, ADLS, Azure Functions, and Key Vault
 * Implement CI/CD pipelines and infrastructure automation using GitHub Actions, Terraform, and DevOps best practices
 * Build and maintain event-driven architectures using Kafka, including CDC and streaming integrations
 * Work with AI/GenAI initiatives involving LLM fine-tuning, RAG, and prompt engineering
 * Monitor, troubleshoot, and optimize data pipeline performance and reliability
 * Collaborate with data architects, analysts, and business stakeholders to translate requirements into technical solutions
 * Ensure data quality, security, and governance standards are met across pipelines
 * Orchestrate and schedule workflows using Airflow