Data and Software Engineer (TS/SCI w/ Poly)
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Summary
On-site data/software engineer in Chantilly, VA building high-throughput, mission-critical data pipelines and cloud infrastructure for a custom enterprise application. Day-to-day work spans Python, Spark, Airflow, Iceberg/Trino Lakehouse tooling, AWS with Terraform, SQL tuning, and geospatial data; current TS/SCI clearance with polygraph is mandatory.
Data and Software Engineer (TS/SCI w/ Poly)
Chantilly, VA 20151
JTEC Consulting LLC is a Veteran-Owned Small Business serving the Defense and Intelligence Communities. Backed by decades of cleared operational experience, we deliver agile, modern technology and data solutions in support of complex mission challenges.
JTEC Consulting LLC is a Veteran-Owned Small Business serving the Defense and Intelligence Communities. Backed by decades of cleared operational experience, we deliver agile, modern technology and data solutions in support of complex mission challenges.
Security Clearance Requirement: Current TS/SCI with polygraph
Location Note: 100% On-Site
Relocation: Relocation support for candidates outside the commuting area will be considered
Position Description:
JTEC Consulting is seeking an experienced Data and Software Engineer to join a focused, agile engineering team building high-throughput, mission-critical data flows for a custom enterprise application. The Data and Software Engineer will design, implement, and optimize end-to-end data architectures, robust ETL/ELT pipelines, and cloud-native infrastructure at scale. Qualified candidates will demonstrate advanced software engineering fundamentals in Python with deep distributed systems expertise, rigorous data governance standards, and modern Lakehouse tooling. A current security clearance with agency-specific polygraph is strictly required for consideration.
Core Responsibilities:
- Pipeline Architecture and Orchestration: Architect, build, and maintain production-grade data pipelines and ETL/ELT workflows using Python, Apache Spark, and workflow orchestration frameworks (e.g., Apache Airflow)
- Lakehouse and Analytics Engineering: Deploy and optimize open table formats (Apache Iceberg) and federated query engines (Trino) to support low-latency analytical queries and large-scale data processing
- Database Design and Performance Tuning: Design relational schemas, maintain indexes, and execute query optimization on MySQL and PostgreSQL for complex analytical workloads
- Geospatial and Complex Data Handling: Ingest, structure, and analyze non-traditional and spatial data formats utilizing indexing systems and spatial extensions like Uber H3 and PostGIS
- Cloud and Infrastructure as Code (IaC): Containerize microservices and batch jobs using Docker or Podman, provisioning and managing scalable AWS resources (S3, Lambda, Step Functions) via Terraform or CloudFormation
- Data Governance, Lineage and Metadata: Implement cataloging and end-to-end operational lineage tracking using Unity Catalog OSS, Apache Polaris, and OpenLineage to satisfy strict compliance, privacy, and security mandates
- AI/ML Model Integration: Collaborate with data science and engineering peers to integrate AI/ML services and operationalize inference models into upstream and downstream data workflows
- Modernization and Migration: Lead technical strategy for large-scale data migrations, schema evolutions, and platform modernization initiatives with minimal system downtime
- Stakeholder Collaboration and Best Practices: Translate ambiguous operational requirements into technical specifications with minimal oversight; author comprehensive technical documentation, establish testing standards, and mentor team members on data engineering design patterns
Education and Qualifications:
- U.S. citizenship
- Current TS/SCI with agency-specific polygraph required for consideration
- Bachelor’s degree in Computer Science, Information Systems, or a related technical discipline (equivalent years of direct experience considered in lieu of a degree)
- 5+ years of progressive experience in data engineering, software engineering, or distributed backend systems
- Effective written and verbal communication skills to support a collaborative, cross-functional team including engineering peers and operational stakeholders
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Demonstrated ability to self-direct and solve complex performance bottlenecks in production distributed environments
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Prior experience delivering platforms within federal, defense, or highly regulated enterprise spaces
Technical Requirements:
- Core Programming:
- Advanced proficiency in Python, including standard scientific and data manipulation libraries (Pandas, NumPy)
- Robust Bash scripting skills for system automation, container startup sequences, and utility pipelines
- Professional familiarity with Java for troubleshooting or extending distributed data systems
- Big Data and Query Engines:
- Deep production experience configuring, deploying, and tuning Apache Spark / PySpark jobs
- Hands-on experience with modern Lakehouse formats (Apache Iceberg) and distributed SQL engines (Trino)
- Cloud and Infrastructure:
- Strong AWS ecosystem expertise, specifically Amazon S3, AWS Lambda, and AWS Step Functions
- Infrastructure as Code (IaC) deployment using Terraform or AWS CloudFormation
- Containerization expertise using Docker or Podman
- Data Stores (RDBMS & NoSQL):
- Advanced SQL capabilities with a proven record of schema design and performance tuning in MySQL and PostgreSQL
- Hands-on experience with NoSQL document or key-value stores (e.g., Amazon DynamoDB)
- Geospatial Analytics:
- Direct working experience manipulating geospatial data leveraging PostGIS and hexagonal hierarchical spatial index frameworks (H3)
- Governance, Metadata and Visualization:
- Experience implementing data catalogs and governance tools such as Unity Catalog OSS or Apache Polaris
- Track record implementing data observability or lineage using OpenLineage
- Experience configuring data visualization layers and business intelligence dashboards using Apache Superset
- Development Operations:
- Version control mastery (Git) and CI/CD automated deployment pipelines
- Solid understanding of data security, privacy principles, role-based access control (RBAC), and regulatory compliance standards
#CJ
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JTEC Consulting LLC provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
Salary:
JTEC offers competitive compensation and benefits to all employees. Salary ranges are advertised based on good faith estimates at the time of posting and indicating pay that JTEC anticipates for successful applicants. The estimated salary range displayed in this posting is dependent upon position requirements, individual qualifications, education, experience, location, and other job-related factors. Our recruiting team will review candidates' related experience and desired salary targets during the evaluation process. All qualified candidates will be considered.
Skills
- Agile
- AI
- Airflow
- Analytics
- Automation
- AWS
- Bash
- CI/CD
- Cloud
- Cloud Native
- CloudFormation
- Containerization
- Data Engineering
- Data Governance
- Data Pipelines
- Data Science
- Data Visualization
- Design Patterns
- Distributed Systems
- Docker
- DynamoDB
- ELT
- ETL
- Git
- Iceberg
- Infrastructure as Code
- Java
- Lakehouse
- Lambda
- Machine Learning
- Microservices
- MySQL
- NoSQL
- NumPy
- Observability
- pandas
- Podman
- PostgreSQL
- PySpark
- Python
- RBAC
- RDBMS
- Regulatory Compliance
- S3
- Spark
- SQL
- Superset
- Terraform
- Trino
- TypeScript
- Unity
- Version Control
- Workflow Orchestration