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Data & Software Engineer TS/SCI (FSP) with Security Clearance

Systech Federal LLCMc Lean, VA🇺🇸United StatesPosted 18 Aug 2026

Why This Role Stands Out

This hybrid role offers a fantastic opportunity to build impactful data solutions within a collaborative team, leveraging advanced Python and cloud technologies to drive innovation. You'll thrive here if you possess strong data engineering skills and a passion for solving complex challenges, with the potential for significant career growth.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

The Data & Software Engineer works with a small team to build complex data flows for a custom application. Successful candidate will have advanced Python programming skills, familiarity with Java, an understanding of data security, privacy, governance and compliance principles and a demonstrated history of building production data pipelines and ETL workflows at scale.

Candidate must have experience: Building end-to-end data pipelines leveraging Python Using orchestration tools to deploy data pipelines, including configuring and updating Spark Jobs
Containerizing and deploying applications in cloud environments like AWS. Working with MySQL and PostgreSQL including performance tuning, schema design, and query optimization for complex, analytical workloads. Leveraging industry standard tools for code control (Git, IaaC control, etc.)
Working with data catalogs, tracking data lineage and handling a variety of data formats, including Geospatial.

Using Bash scripting for automation and data processing tasks
Integrating Al/ML services and models *This role requires an active TS/SCI FSP to start*

Required Skills: Minimum of 5 years' experience with: · Apache Spark & PySpark · Advanced Python skills (including Pandas & NumPy) · Docker, Podman · AWS S3, Lambda & Step functions · Apache Iceberg, Airflow, etc. · SQL (with Trino) · NoSQL, DynamoDB · Unity Catalog OSS, Apache Polaris · Apache Superset · Terraform or CloudFormation · OpenLineage · H3, PostGIS Responsibilities: Work with stakeholders to understand data requirements, assess feasibility, and design appropriate solutions with minimal oversight
Leverage strong problem-solving and debugging skills for data quality issues, pipeline failures, and performance bottlenecks
Leverage a background in large-scale data migration or platform modernization efforts
Contribute to data engineering documentation, best practices, and design patterns.

Skills

Docker
DynamoDB
MySQL
SQL
AWS
ETL
NumPy
Airflow
Apache
Apache Spark
Bash
CloudFormation
Git
Java
Pandas
PostgreSQL
Python
Terraform
Unity

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