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# Data Engineer

- **Company:** Procyon Corporation
- **Location:** Pittsburgh, PA, United States
- **Experience:** Experienced
- **Salary:** $104,000.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Microsoft Azure, Cloud Computing, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Mining, Data Security, Data Warehousing, Amazon DynamoDB, Python (Programming Language), PostgreSQL, Microsoft SQL Server, MongoDB, MySQL, NoSQL, Redis, SQL Databases, Scripting, Data Storage Technologies, Snowflake, Apache Spark, Cassandra, Apache Kafka, Non-relational Database, Data Management, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** June 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=816452e4692ec940

## About the Role

Do you have experience in Schema design?, Skills: Python | SQL | NoSQL

Experience: 3-7 Years Employment Type: Full Time / Contract Work Mode: Onsite, * Strong proficiency in Python for data engineering and automation

 * Hands-on experience with SQL databases (PostgreSQL, MySQL, MS SQL Server)
 * Experience with NoSQL databases (MongoDB, Cassandra, DynamoDB, or Redis)
 * Knowledge of data warehousing concepts and data modeling
 * Experience with big data tools (Spark, Kafka, Airflow) is a plus
 * Familiarity with cloud platforms (AWS, Azure, or GCP)
 * Strong problem-solving and analytical skills

Nice to Have

 * Experience with dbt, Snowflake, or Databricks
 * Knowledge of data governance and data quality frameworks
 * Exposure to machine learning pipelines

## Description

We are looking for a talented and experienced Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support business intelligence and analytics needs., * Design, develop, and maintain robust data pipelines and ETL/ELT processes

 * Build and optimize data models for both relational and non-relational databases
 * Write efficient Python scripts for data extraction, transformation, and loading
 * Collaborate with data scientists and analysts to understand data requirements
 * Ensure data quality, consistency, and integrity across all data platforms
 * Monitor and troubleshoot data pipeline performance and failures
 * Implement best practices for data security and governance
 * Work with cloud platforms (AWS/Azure/GCP) for data storage and processing


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