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# Mid-Level ETL Engineer [$310k/yr+] TS/SCI-FS Poly

- **Company:** SYSTOLIC, INC.
- **Location:** Annapolis Junction, MD, United States
- **Experience:** Experienced
- **Salary:** $310,000
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Automation of Tests, Big Data, Data Governance, Extract Transform Load (ETL), Data Stores, DevOps, Memory Management, Amazon DynamoDB, Elasticsearch, Python (Programming Language), PostgreSQL, NoSQL, Performance Tuning, Data Streaming, Load Balancing, Cloud Platform System, Real Time Systems, Apache Nifi, Restful APIs, Data Pipelines
- **Published:** October 30, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9275558/mid-level-etl-engineer-310kyr-tssci-fs-poly

## About the Role

* Degree: Technical bachelor's degree or equivalent experience
 * Years of experience: 12+ years
 * Total Compensation: $310k+ yearly (tentative)

## Description

* Develop and manage enterprise-level ETL data pipelines utilizing Apache NiFi, Java, and Python.
 * Build, optimize, and troubleshoot large-scale data ingestion and transformation flows across AWS cloud environments.
 * Integrate relational and NoSQL data stores via RESTful web services within a DevOps software development lifecycle., * Develop and implement enterprise-level ETL NiFi data pipelines for large-scale data ingestion, transformation, and processing from diverse sources.
 * Optimize NiFi data flows, including processor tuning, memory management, and load balancing for batch and real-time processing.
 * Identify, diagnose, and resolve data flow performance bottlenecks, discrepancies, and integration failures.
 * Follow established best practices for development, deployment, security, and enterprise data governance.
 * Develop automation scripts and custom processors using Java and Python.
 * Integrate RESTful web services and interact with relational and NoSQL databases, including PostgreSQL, DynamoDB, and Elasticsearch.
 * Deploy, monitor, and maintain ETL solutions across cloud environments including AWS.
 * Collaborate with cross-functional teams to translate technical requirements into scalable data architectures.