Senior Data Engineer - Secret Clearance Required

Description

The company is a global technology and professional services firm with 26,000 staff in more than 50 countries. It serves U.S. government, defense and intelligence agencies with AI, cloud, cyber and software development work.

You will join a team of software engineers, AI/ML engineers, cybersecurity specialists, database administrators and enterprise architects who build secure, scalable and reliable data solutions for highly controlled government environments.

The role needs a Secret clearance that you currently hold, and you must be able to obtain one.

Responsibilities

• Chatbot and AI platform data engineering: design, build and maintain the data infrastructure behind the chatbot and related AI applications.
• Run and tune PostgreSQL databases, including the pgvector extension for vector similarity search.
• Build and maintain ingestion pipelines for structured, semi-structured and unstructured data.
• Connect document processing tools such as Docling and Tesseract to automated pipelines.
• Support extraction, transformation, validation, indexing and storage of document metadata.
• Work with AI/ML engineers to improve data retrieval, embedding storage and RAG workflows.
• Write Python services, scripts and APIs that move data between systems.
• Help move database services and related components into Podman containers.
• Improve database reliability, performance, observability, backups and recovery.
• Troubleshoot data integration problems across application services, databases and AI inference systems.
• Enterprise data integration and data fabric: help assess and design a possible enterprise data fabric architecture.
• Build integrations that connect data across applications, databases and enterprise systems.
• Design reusable pipelines and integration patterns that serve several applications and business areas.
• Help develop data catalogs, metadata management, lineage and discovery tools.
• Assess data virtualization, data federation and distributed data access approaches.
• Set up and enforce data quality, consistency, validation and governance controls.
• Work with enterprise architects and stakeholders to define integration needs and technical solutions.
• Help create common data models, integration standards and reusable data services.
• Assess open-source and commercial integration tools for use in secure government settings.
• Data migration and modernization: plan and carry out migrations from legacy systems to modern databases and enterprise applications.
• Assess source systems, schemas, data quality, dependencies and migration requirements.
• Build ETL and ELT pipelines with Python, SQL and suitable integration frameworks.
• Extract, transform, cleanse, map, reconcile and validate data.
• Design repeatable migration processes that keep operational risk and data loss low.
• Support migration testing, performance tuning, rollback planning and post-migration checks.
• Write scripts and automation for routine migration tasks.
• Produce technical documentation, migration plans, data mapping specifications and operating procedures.
• Infrastructure, automation and security: build and support containerized data services with Podman and orchestration tools.
• Support applications and databases on Red Hat Enterprise Linux and Windows Server.
• Automate database deployment, configuration, monitoring and upkeep.
• Put secure data access controls, encryption, audit logging and data handling practices in place.
• Support software and data service deployments in air-gapped and classified environments.
• Work with cybersecurity and infrastructure teams to meet applicable federal security requirements.
• Take part in vulnerability fixes, software evaluation, change management and accreditation support.
• Build monitoring and operational logging with tools such as Splunk.

Requirements

• A bachelor's degree in computer science, data engineering, information systems, software engineering or a related technical field, or equivalent practical experience.
• 7+ years of experience in data engineering, database development, data integration or related software engineering work.
• Strong Python skills for data processing, scripting, automation and service integration.
• Advanced SQL, including query optimization, schema design and performance tuning.
• Experience administering, building on or optimizing PostgreSQL or a comparable enterprise relational database.
• Proven experience designing and implementing ETL and ELT pipelines.
• Experience with enterprise data migrations, covering mapping, transformation, validation and reconciliation.
• Familiarity with REST APIs, JSON and structured and semi-structured data formats.
• Experience with Linux administration, shell scripting and deployment automation.
• Understanding of data modeling, relational databases, data integrity and data lifecycle management.
• Experience with Git, automated testing and modern development practices.
• Ability to design, document and troubleshoot complex data workflows.
• Strong communication skills and the ability to work across multidisciplinary engineering teams.
• 10+ years of related experience.
• Secret clearance currently held, with the ability to obtain Secret.
• Preferred: experience supporting AI/ML platforms, LLM applications or Retrieval-Augmented Generation solutions.
• Preferred: familiarity with vector databases, pgvector, embeddings and semantic search.
• Preferred: experience with document ingestion and content extraction tools such as Docling, Apache Tika or Tesseract.
• Preferred: experience with container technologies such as Podman or Docker.
• Preferred: familiarity with Redis and PgBouncer.
• Preferred: experience with enterprise data fabric, data mesh or data virtualization architectures.
• Preferred: experience with Apache Airflow, Apache NiFi or similar pipeline orchestration frameworks.
• Preferred: experience with Apache Kafka or other event-driven integration technologies.
• Preferred: familiarity with data catalogs, metadata management, lineage and governance frameworks.
• Preferred: experience with cloud or hybrid data platforms, including AWS or Azure.
• Preferred: experience modernizing legacy databases and enterprise data platforms.
• Preferred: familiarity with secure, disconnected, air-gapped or classified IT environments.
• Preferred: knowledge of federal cybersecurity standards, RMF processes and Authority to Operate (ATO) requirements.
• Preferred: experience with Splunk, automated testing and CI/CD practices.

Conditions

Onsite work in Sterling, Virginia, USA.

40 scheduled hours per week.

Travel of less than 10%.

U.S. citizenship required.

No Public Trust or other clearance required beyond Secret.

Salary is likely to fall between $153,000 and $207,000. This is not a guarantee. Pay is set by experience, geographic location and possibly contract terms, and may fall outside this range.

As part of hiring, you will complete an identity verification check using biometrics and AI, and you must be on camera for virtual interviews. The company may photograph you to verify identity and prevent fraud, and by proceeding you consent to the collection and use of your biometric data for that purpose and for security.

The company is an equal opportunity employer and welcomes applications from individuals with disabilities and protected veterans.

Benefits

• Medical plans, some with Health Savings Accounts, plus dental and vision plans.
• A 401(k) that accepts pre-tax and post-tax contributions up to IRS annual limits, with a company match.
• Full flex work weeks where possible, to support work-life balance.
• Paid time off including vacation, sick and personal time, holidays, paid parental leave, military leave, bereavement and jury duty.
• Short- and long-term disability, life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance, provided or available.