Fantom

Systems integration and IT services, analytics

Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeMcLean, VA, USANo salary listed

About the Job

Requirements

Must be fully cleared with a recent polygraph.
Must be willing and able to work fully onsite at the location listed in the posting.
Have 5 or more years of experience as a data engineer, software engineer, or similar technical role.
Demonstrate experience building production-scale data pipelines and ETL/ELT workflows.
Have advanced Python programming experience, including libraries such as Pandas and NumPy.
Have strong experience with Apache Spark and PySpark for distributed data processing.
Have experience with workflow orchestration tools such as Apache Airflow or AWS Step Functions.
Have experience deploying containerized applications using Docker, Podman, or similar technologies.
Have experience developing cloud-native applications within AWS environments.
Have hands-on experience with AWS services including Amazon S3, AWS Lambda, and AWS Step Functions.
Have strong experience with PostgreSQL and MySQL, including schema design, performance tuning, and query optimization.
Have advanced SQL skills supporting large-scale analytical workloads.
Have experience with Git and CI/CD practices for data engineering and software deployment.
Understand data governance, privacy, security, and compliance principles.
Have strong analytical, troubleshooting, and problem-solving skills.
Have experience collaborating directly with stakeholders to gather requirements and deliver technical solutions with minimal oversight.

Responsibilities

Design, develop, and maintain scalable, end-to-end data pipelines and ETL/ELT workflows supporting enterprise applications.
Build and optimize distributed data processing solutions using Apache Spark and PySpark.
Develop robust Python applications and automation scripts to support data engineering initiatives.
Deploy and manage data pipelines using workflow orchestration platforms such as AWS Step Functions or Apache Airflow.
Containerize and deploy data applications within AWS cloud environments using Docker, Podman, or similar technologies.
Design, optimize, and maintain PostgreSQL and MySQL databases, including schema design, indexing, and query optimization for analytical workloads.
Collaborate with stakeholders to gather requirements, assess technical feasibility, and design scalable data solutions.
Troubleshoot and resolve data quality issues, pipeline failures, and performance bottlenecks.
Implement and support data governance, security, privacy, and compliance best practices.
Develop and maintain technical documentation, architecture diagrams, and engineering standards.
Support large-scale data migration and platform modernization initiatives.
Integrate AI/ML services, machine learning models, and advanced analytics capabilities into enterprise data platforms.
Utilize Git and CI/CD pipelines to support automated testing, deployment, and version control.

Desired Qualifications

Have experience designing and implementing Lakehouse architectures using Apache Iceberg.
Have experience configuring and supporting enterprise data platform technologies, including Apache Ranger, Trino, Apache Polaris or Unity Catalog OSS, and Apache Superset.
Have experience with Infrastructure as Code using Terraform or AWS CloudFormation.
Have proficiency with Bash scripting for automation and operational support.
Have experience tracking data lineage using OpenLineage or similar tools.
Have working knowledge of Java.
Have experience implementing data quality frameworks, automated testing, and validation strategies.
Have experience supporting enterprise data modernization and large-scale migration initiatives.
Have experience integrating AI/ML services, including OCR, NLP, speech-to-text, language detection, translation services, topic modeling, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) pipelines.
Have experience processing geospatial data using technologies such as H3, PostGIS, or similar frameworks.
Have experience with NoSQL databases such as DynamoDB.
Have experience developing engineering standards, documentation, and reusable design patterns.

Fantom Corporation is a mission-focused organization supporting critical programs across the defense and intelligence community. We partner with our customers to deliver high-impact technical solutions while fostering a culture built on trust, expertise, and long-term career growth.

We are seeking a Data & Software Engineer to join a small, agile team developing advanced data solutions for a custom application supporting mission-critical operations. This role is focused on designing, building, and optimizing scalable data pipelines and ETL workflows while leveraging modern cloud technologies, distributed data processing frameworks, and AI/ML capabilities.

The ideal candidate has strong Python programming skills, experience building production-grade data pipelines, and expertise with Apache Spark, AWS cloud services, relational databases, and modern data engineering best practices.

Responsibilities

Design, develop, and maintain scalable, end-to-end data pipelines and ETL/ELT workflows supporting enterprise applications
Build and optimize distributed data processing solutions using Apache Spark and PySpark
Develop robust Python applications and automation scripts to support data engineering initiatives
Deploy and manage data pipelines using workflow orchestration platforms such as AWS Step Functions or Apache Airflow
Containerize and deploy data applications within AWS cloud environments using Docker, Podman, or similar technologies
Design, optimize, and maintain PostgreSQL and MySQL databases, including schema design, indexing, and query optimization for analytical workloads
Collaborate with stakeholders to gather requirements, assess technical feasibility, and design scalable data solutions
Troubleshoot and resolve data quality issues, pipeline failures, and performance bottlenecks
Implement and support data governance, security, privacy, and compliance best practices
Develop and maintain technical documentation, architecture diagrams, and engineering standards
Support large-scale data migration and platform modernization initiatives
Integrate AI/ML services, machine learning models, and advanced analytics capabilities into enterprise data platforms
Utilize Git and CI/CD pipelines to support automated testing, deployment, and version control

Required Qualifications

Must be fully cleared with a recent polygraph
Must be willing and able to work fully onsite at the location listed in this posting
5+ years of experience as a Data Engineer, Software Engineer, or similar technical role
Demonstrated experience building production-scale data pipelines and ETL/ELT workflows
Advanced programming experience with Python, including libraries such as Pandas and NumPy
Strong experience with Apache Spark and PySpark for distributed data processing
Experience with workflow orchestration tools such as Apache Airflow or AWS Step Functions
Experience deploying containerized applications using Docker, Podman, or similar technologies
Experience developing cloud-native applications within AWS environments
Hands-on experience with AWS services including Amazon S3, AWS Lambda, and AWS Step Functions
Strong experience with PostgreSQL and MySQL, including schema design, performance tuning, and query optimization
Advanced SQL skills supporting large-scale analytical workloads
Experience with Git and CI/CD practices for data engineering and software deployment
Understanding of data governance, privacy, security, and compliance principles
Strong analytical, troubleshooting, and problem-solving skills
Experience collaborating directly with stakeholders to gather requirements and deliver technical solutions with minimal oversight
#CJ

Desired Qualification

Experience designing and implementing Lakehouse architectures using Apache Iceberg
Experience configuring and supporting enterprise data platform technologies, including:
- Apache Ranger
- Trino
- Apache Polaris or Unity Catalog OSS
- Apache Superset
- Experience with Infrastructure as Code (Terraform or AWS CloudFormation)
- Proficiency with Bash scripting for automation and operational support
- Experience tracking data lineage using OpenLineage or similar tools
- Working knowledge of Java
- Experience implementing data quality frameworks, automated testing, and validation strategies
- Experience supporting enterprise data modernization and large-scale migration initiatives
- Experience integrating AI/ML services, including OCR, NLP, speech-to-text, language detection, translation services, topic modeling, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) pipelines
- Experience processing geospatial data using technologies such as H3, PostGIS, or similar frameworks
- Experience with NoSQL databases such as DynamoDB
- Experience developing engineering standards, documentation, and reusable design patterns

Fantom Corp is a Software Development, Agile Cloud, Software Development, Cyber Security (Risk Management, Assessments & Authorization (A&A)), Data, AI Platform (Computer Vision Models), Podcasting Media Services, and IT Services provider. Established in 2015, Fantom Corp serves Federal customers with top-notch Cybersecurity Architects, Data Scientists/Analysts, Software Engineers/Developers, DevSecOps Engineers, Project Managers, Identity, Credential Access Management (ICAM) services , and Cloud-certified practitioners. We excel in delivering emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML) with a focus on identifying trends, object detection, and classification of structured and unstructured data. Fantom Corp possesses mastery in all aspects of digital audio production. We lead in the ideation and creation of efforts for clients who want to harness the power of podcasting. We guide them in selecting the right show format for their needs and goals. As a Small Business, we possess the innovation, speed and flexibility to meet your requirements.

About the Company

Fantom

Systems integration and IT services, analytics

Fantom leads IT services for federal and commercial clients, focusing on big data analytics, system integration, software engineering, and technical consulting. Its offering blends architecture and program management with data-driven capabilities to help organizations detect patterns, uncover trends, and derive actionable insights from structured and unstructured data. Projects are delivered through service contracts and fixed engagements, supported by a team of architects, engineers, and program managers. What sets Fantom apart is its minority-owned status combined with a dual focus on Department of Defense and Intelligence Community work alongside private-sector clients, and its emphasis on employee well-being through benefits like profit-sharing and life insurance. The company's goal is to enable clients to make informed decisions and achieve mission and business objectives by providing specialized IT solutions and data-driven capabilities.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: Leesburg, VA
Founded: 2014

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