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1mo ago

Data Scientist/Machine Learning Engineer

CATHEXIS Tysons, VA

Tysons, VA

1mo ago Closed

$120k - $150k/yr Full time Artificial Intelligence Big Data Cloud Platforms

This position is no longer accepting applications (closed Nov 1, 2026).

Job Description

CATHEXIS is hiring a Data Scientist/Machine Learning Engineer to research, design, implement, and deploy machine learning algorithms for enterprise applications while supporting federal customers in building their own tools for digital transformation. Based in Tysons, VA (onsite), this role blends hands-on ML work with customer enablement in an environment built for autonomy, teamwork, and impact.

What you’ll do

Research, design, implement, and deploy machine learning algorithms for enterprise applications.
Assist and enable federal customers to build their own applications.
Contribute to the design and implementation of new features.

What you’ll bring

Active Secret clearance or above is required.
Bachelor’s degree in Computer Science, Electrical Engineering, Statistics, or an equivalent field.
MS or PhD in a related field is preferred.
3+ years of relevant work experience preferred (3 to 5 years desired).
Strong Python programming skills.
Applied Machine Learning experience across regression and classification, including supervised and unsupervised learning.
Strong mathematical foundation in linear algebra, calculus, probability, and statistics.
Experience with scalable ML such as MapReduce and streaming.
Ability to drive work independently and in a team, with an execution-oriented, quality-focused mindset.
Excellent verbal and written communication, including the ability to explain technical concepts to both technical and non-technical audiences.
Ability to work on multiple concurrent projects in an agile environment.

Tools you’ll work with

Python, MapReduce, and major cloud platforms including AWS, Microsoft Azure, and Google Cloud Services.

Benefits

Performance bonuses
Medical, Dental, and Vision insurance
401(k) plan (Traditional and Roth)
Life Insurance (Basic, Voluntary & AD&D)
Paid Time Off and 11 Federal Holidays
Parental Leave
Commute benefits
Short Term & Long Term Disability
Training & Development
Wellness Program
Community Outreach Initiatives

Desired experience

Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers (AWS, Azure, or Google Cloud Services).
Experience leveraging modern LLM tools to accelerate development workflows and improve code quality.
Experience with deep learning, including natural language processing, computer vision, or reinforcement learning.

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1mo ago

Senior Full Stack Data Engineer

All IT Solutions Arlington, VA

Arlington, VA

1mo ago Closed

Contract Backend Developer Senior Big Data

This position is no longer accepting applications (closed Oct 31, 2026).

Job Description

All IT Solutions is seeking a Senior Full Stack Data Engineer for a client engagement delivering scalable data platforms and data-intensive, analytics-driven applications across application, service, and data-processing layers. This contract role is hybrid in Arlington, VA, USA, with opportunities to collaborate with cross-functional teams, contribute to engineering best practices, and continuously grow as technologies evolve.

Responsibilities

Contribute to the architecture, design, and development of scalable data platforms and data-intensive applications.
Work across application, service, and data-processing layers using technologies such as Java/Spring Boot, React, TypeScript, Databricks, Spark, Hadoop, and related platforms.
Collaborate within your immediate team and across development teams to align on shared goals, support cross-cutting initiatives, and deliver cohesive, enterprise-grade solutions.
Participate in design and code reviews, contribute to engineering best practices, and support operational excellence.
Work effectively across global time zones, help maintain a strong engineering culture, and continuously build technical skills while delivering reliable, high-quality software.
Build full-stack features for business value, including capabilities that support data onboarding, exchange, discovery, and consumption.
Design, build, and maintain scalable data platforms, distributed systems, and enterprise integration solutions across on-premises and cloud environments.
Develop and optimize data-intensive applications using Databricks, Spark, and related platforms for efficient processing, transformation, and serving of data.
Identify and resolve performance bottlenecks across services, APIs, data-processing workloads, and user experience.
Collaborate with Product, Engineering, Data Governance, Security, and business stakeholders to understand and deliver requirements.
Mentor and support team members while contributing to a collaborative, growth-oriented engineering culture.
Continuously learn and improve, staying current with technologies and driving enhancements in quality, scalability, and developer productivity.

Requirements

Bachelor’s degree in computer science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.
Data engineering and processing experience using Databricks / Hadoop with PySpark / SQL.
Java (backend) plus React / TypeScript (frontend), along with CI/CD, testing, and optimization.
Experience with Data Governance and security, including using reusable frameworks.
Experience as a full-stack Software Engineer, with exposure to platforms built using modern technologies such as Java/Spring Boot, TypeScript, and React.
Experience building large-scale data platforms and distributed systems, plus enterprise integration across on-premises and cloud environments, leveraging technologies such as Spark, Kafka, Flink, NiFi, Hadoop/Cloudera, Databricks, and modern cloud-native data services.
Experience integrating AI-driven capabilities into data platforms, with governance and guardrails for emerging use cases, including agentic commerce.
Experience building reusable platforms that serve multiple products, teams, or business domains.
Foundational understanding of software engineering principles including object-oriented programming, API design, and scalable system design.
Interest in data-intensive applications, with focus on performance, scalability, and reliability across services and data-processing layers.
Strong collaboration and communication skills to work effectively with cross-functional teams.
Curiosity and self-motivation with a growth mindset, and willingness to learn while solving analytical, data-driven problems in an agile, fast-paced environment.

Preferred Qualifications

Master’s degree in computer science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.

Technologies

Java, Spring Boot, React, TypeScript
Databricks, Spark, Hadoop, PySpark, SQL
CI/CD, Kafka, Flink, NiFi
Hadoop/Cloudera, Cloudera
Cloud-native data services

Apply: Apply Now

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1mo ago

AI/ML Data Engineer

Precise Software Solutions Incorporated Washington, DC

Washington, DC

1mo ago Closed

Full time Apache Airflow Artificial Intelligence Azure

This position is no longer accepting applications (closed Oct 31, 2026).

Job Description

Precise Software Solutions Incorporated is hiring an AI/ML Data Engineer in Washington, DC for an onsite role supporting the U.S. Government. This position focuses on designing and governing the data foundation that enables secure AI-enabled applications, with end-to-end ownership of AI-ready datasets and measurable, secure AI operations.

What You’ll Do

Design and maintain data ingestion, transformation, and processing pipelines (ETL/ELT) for AI training, evaluation, retrieval, and operations, including support for data migration and cleansing.
Curate, validate, and version datasets while maintaining dataset inventories, metadata, lineage, provenance, and ingestion logs.
Implement automated data-quality checks for duplication, schema changes, completeness, and freshness; maintain dataset quality scorecards and drift reports.
Design data models, vector stores, and embedding schemas for Retrieval-Augmented Generation (RAG) knowledge bases, including re-indexing content when sources change.
Measure retrieval and model quality against established baselines using metrics such as precision/recall, MRR, NDCG, and context relevance.
Prepare data-related deliverables, including AI model cards, ML and AI pipeline documentation, RAG/AI pipeline evaluation reports, data dictionaries, embedding schema documentation, and responses to Government data calls.
Build secure structured-data access for AI applications such as natural-language-to-SQL with query validation and role-based authorization, and support dashboards and operational analytics.
Monitor data and ML pipelines, troubleshoot failures, and support root-cause analysis while keeping data in FedRAMP-authorized cloud regions using FIPS-validated encryption.
Support Responsible AI by preparing representative evaluation datasets, testing AI outputs for bias, accuracy, and hallucination, and documenting results to align with federal AI governance requirements.
Secure the AI data path from source datasets and embeddings to prompts and logs, including support for AI risk testing such as data poisoning.

Required Qualifications

Bachelor’s degree in Computer Science, Engineering, Mathematics, Information Systems, or a related field and 5+ years of relevant experience; equivalent experience may substitute for the degree.
5+ years of hands-on data engineering or database development experience, including data modeling, SQL, and ETL/ELT pipeline development.
Strong proficiency in Python and experience with data processing frameworks such as pandas and Spark, plus workflow orchestration tools such as Airflow.
1+ year preparing data for Generative AI or machine learning, including embeddings, vector databases, RAG knowledge bases, or training and evaluation datasets.
Experience implementing data quality, lineage, metadata management, and data governance controls.
Experience protecting sensitive data (PII), including masking, minimization, and access controls.
Experience with a major cloud data platform (AWS, Azure, or Google Cloud), Git, and CI/CD tools.
Must be a U.S. citizen or lawful permanent resident (green card holder).
Must reside in the Washington, DC metropolitan area and be able to work onsite at Government offices.
Must be able to obtain and maintain a Public Trust background investigation.

Technology Stack

Python, pandas, Spark, Airflow, AWS, Azure, Google Cloud, Git, CI/CD
Vector stores, vector databases, pgvector, OpenSearch
FIPS-validated encryption, FedRAMP-authorized cloud regions
Natural-language-to-SQL

Benefits

Comprehensive Health Benefits (Medical, Dental and Vision)
Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
Retirement Plan with 4% match and discretionary match at year end
Paid Time Off (PTO): 15 days of PTO accrued per year; 7 holidays + 3 Floating holidays; 2 Innovation days (paid training days)
Short Term and Long-Term Disability
Paid Parental Leave
Paid Jury Duty leave
Life and AD&D Insurance
Critical Illness Insurance
Training and Development
Wellness Incentives & Discount programs
Employee Referral Program
Annual Charity Donation Match
Awards and Recognition

Preferred Qualifications

Master’s degree in a related field and 7+ years of data engineering experience, including support of federal agency programs.
Experience evaluating retrieval quality and building RAG pipelines with vector stores (e.g., pgvector, OpenSearch).
Experience with MLOps tooling, including model and dataset versioning, feature stores, or model registries.
Generative AI, LLM security, or data certification (e.g., Databricks Generative AI Engineer, Snowflake SnowPro, AWS, Microsoft Azure, or Google Cloud).
An active Public Trust or prior federal background investigation.

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1mo ago

Business Analytics Engineer

Cushman & Wakefield Creve Coeur, MO

Creve Coeur, MO

1mo ago Closed

$106k - $125k/yr Full time Analytics Arcgis Online Artificial Intelligence

This position is no longer accepting applications (closed Oct 31, 2026).

Job Description

Business Analytics Engineer will design, develop, and maintain data, analytics, reporting, and geospatial solutions that support real estate portfolio decisions.

Responsibilities

Develop and maintain reporting, analytics, and geospatial solutions to improve visibility into portfolio performance, workplace trends, operational metrics, and business outcomes
Transform, validate, and manage data from multiple sources to support portfolio intelligence, operational reporting, forecasting, and decision support
Partner with business stakeholders, account teams, and clients to translate business requirements into reusable technical solutions
Support portfolio planning, workplace strategy, occupancy analysis, location intelligence, and operational decision-making through insight generation and visualization
Identify opportunities to improve efficiency through automation, standardization, and adoption of emerging technologies, including AI-enabled tools
Support the continued evolution of PAG’s analytics, reporting, geospatial, and technology capabilities
Build and maintain dashboarding and reporting solutions for portfolio performance, workplace strategy, occupancy trends, operational efficiency, and service delivery using Power BI, Looker, Tableau, or similar platforms
Create and maintain data pipelines, transformation processes, and data models that support analytics and reporting solutions, with Databricks experience strongly preferred
Integrate data from internal systems, client platforms, commercial real estate technologies, and external sources
Develop and maintain ArcGIS Online environments, maps, dashboards, and geospatial data products for location intelligence, market analysis, portfolio optimization, workplace planning, and operational decision-making
Identify opportunities to automate repetitive reporting, data preparation, and operational processes
Leverage AI-enabled tools to improve productivity, accelerate development, and enhance analytics capabilities
Communicate technical concepts clearly to both technical and non-technical audiences
Support user adoption, training, documentation, and continuous improvement efforts

Requirements

3-7 years of experience in business analytics, business intelligence, analytics engineering, reporting, data engineering, or related fields
Experience developing dashboards, reporting solutions, and analytical products used by business stakeholders
Experience with business intelligence platforms including Power BI, Tableau, Looker, or similar tools
Experience building and maintaining data pipelines within modern cloud analytics platforms, with Databricks experience strongly preferred
Strong problem-solving, analytical thinking, and data interpretation skills
Experience gathering requirements and working directly with business stakeholders
Ability to translate business requirements into technical solutions and explain complex concepts to business stakeholders, account teams, and clients
Excellent written and verbal communication skills
Experience with Databricks, Delta Lake, Unity Catalog, or modern cloud-based analytics platforms
Experience using Python for analytics, automation, reporting, or workflow development
Experience supporting commercial real estate, corporate real estate, portfolio planning, workplace strategy, occupancy management, facilities management, or related business functions
Experience with ArcGIS Online, ESRI products, or geospatial analytics platforms
Experience within consulting, professional services, or client-facing environments
Experience leveraging AI-enabled tools such as Microsoft Copilot, Claude, Gemini, ChatGPT, or similar technologies
Experience working with enterprise reporting, operational analytics, portfolio analytics, workplace analytics, or business performance management

Technologies

Power BI, Looker, Tableau
Databricks
ArcGIS Online, ESRI
SQL, Python
Delta Lake, Unity Catalog
Microsoft Office Suite (Excel, PowerPoint, Word)
Google Workspace (Sheets, Docs, Slides)
Microsoft Copilot, Claude, Gemini, ChatGPT

Location

Creve Coeur, MO (onsite)

Compensation

USD 106,250 - 125,000 per year

Education

Bachelor’s degree in Data Analytics, Information Systems, Computer Science, Business, Geography/GIS, Engineering, Mathematics

Benefits

Health, vision, and dental insurance
Flexible spending accounts
Health savings accounts
Retirement savings plans
Life and disability insurance programs
Paid and unpaid time away from work
Competitive pay (varies by eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements)
Opportunity to enroll in a variety of benefit programs

What “Success” Looks Like

Stakeholders trust the data, reporting, and analytics solutions used for business and real estate decisions
Reporting and analysis processes become more automated, scalable, and consistent
Business users spend less time gathering, validating, and preparing data and more time acting on insights
Analytics and geospatial solutions become integrated into standard account operations and decision-making
Stakeholders use reporting, analytics, and geospatial solutions to support portfolio planning, occupancy strategy, location decisions, operational performance, and workplace initiatives

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1mo ago

Data Engineer

Everforth ECS Fairfax, VA

Fairfax, VA

1mo ago Closed

$100k - $115k/yr Full time Data Engineer Data Integration Data Pipeline

This position is no longer accepting applications (closed Oct 31, 2026).

Job Description

Everforth ECS is seeking a Data Engineer to support day-to-day data operations for the Chief Digital and Artificial Intelligence Office (CDAO) within the Secure Unclassified Network (SUNet).

Responsibilities

Support ingestion, organization, storage, management, and secure transport of structured and unstructured data within the SUNet environment.
Carry out approved data transfers between authorized systems, storage locations, enclaves, and users while following established security, data-handling, and customer requirements.
Validate data transfers using manifests, file counts, checksums, metadata, or other verification methods to confirm completeness and integrity.
Maintain data inventories, metadata, storage locations, access information, transfer records, and supporting documentation for visibility into SUNet data holdings.
Assist with on-premises and cloud data storage resource management, including monitoring capacity, organizing datasets, identifying storage needs, and supporting data lifecycle activities.
Create, submit, coordinate, track, test, document, and close Change Requests related to data operations, system configurations, access requirements, and customer-requested capabilities.
Implement assigned customer requirements by translating operational needs into data-management actions, technical tasks, configuration changes, or process improvements under senior technical guidance.
Support onboarding of new government and commercial users, data sources, and development teams by coordinating data access, identifying required datasets, and assisting with approved data-transfer workflows.
Troubleshoot routine issues for data access, permissions, file transfers, storage capacity, connectivity, data availability, and related services, escalating more complex problems as needed.
Develop basic scripts and automation using Python, Bash, PowerShell, or similar tools to improve repeatable data-management, validation, transfer, and reporting processes.
Develop and maintain technical documentation, including SOPs, data-flow diagrams, data inventories, transfer procedures, troubleshooting guides, Change Request documentation, and operational runbooks.
Support special projects, data migrations, capability demonstrations, testing events, process improvements, and other technical activities for CDAO, government partners, and commercial AI/ML teams.

Requirements

Autonomous self-starter with a proven track record delivering complex data solutions independently and resolving engineering hurdles with minimal supervision.
Preferred certifications at hire or within 6–12 months:
- CompTIA Security+
- CompTIA Linux+
- AWS Solutions Architect – Associate
Network+ or equivalent networking fundamentals certification.

Technologies

Python
Bash
PowerShell
CompTIA Security+
CompTIA Linux+
AWS Solutions Architect – Associate
Network+

Location

Fairfax, VA (onsite)

Salary

$100,000 - $115,000 per year (USD)

Benefits

Everforth ECS benefits

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1mo ago

Mid-Level Data Engineer

Everforth ECS Remote 🌍 Remote

Remote

1mo ago Closed

$130k - $140k/yr Full time Data Analytics Data Engineer Data Integration

This position is no longer accepting applications (closed Oct 31, 2026).

Job Description

Everforth ECS is hiring a Mid-Level Data Engineer to support a high-priority DHS OCIO data analytics and business intelligence platform from a remote setup.

Responsibilities

Deliver end-to-end development across data pipelines for storing, managing, and provisioning data to consumers
Collaborate with data scientists, data architects, and federal stakeholders to deploy models into production
Write code to maintain performance and reliability for data extraction and processing
Support ongoing automation for data ingest
Demonstrate technical excellence by applying lean-agile engineering principles such as API-first design, simple design, continuous integration, version control, and automated testing
Work with program management and engineers to implement and document complex, evolving requirements
Contribute to a culture focused on customer service excellence, innovation, collaboration, and teamwork
Partner in a cross-functional environment with user experience researchers and designers, product managers, engineers, and other specialists

Requirements

US Citizenship required
Ability to obtain a Public Trust Clearance
7+ years of IT experience, including experience working with modern cloud data warehouse technologies
Experience designing table models
Experience ingesting multiple data types into the Redshift data warehouse
Proficiency developing ETL processes, including test and validation steps
Proficiency manipulating data using Python, R, SQL, and SAS
Strong knowledge of big data analysis and storage tools and technologies
Strong understanding of agile principles and the ability to apply them
Experience working within the AWS ecosystem
Experience with relational databases (e.g., PostgreSQL)
Comfort working with version control systems (e.g., Git)

Technologies

AWS
Redshift
Python
R
SQL
SAS
PostgreSQL
Git
ETL

Location

Remote

Compensation

USD 130,000 - 140,000 per year

Benefits

Benefits - Everforth ECS

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1mo ago

Data Engineer

Space Dynamics Laboratory Stafford, VA

Stafford, VA

1mo ago Closed

$108k - $208k/yr Full time Data Data Analysis Data Analytics

This position is no longer accepting applications (closed Oct 31, 2026).

Job Description

Space Dynamics Laboratory (SDL) is seeking a Data Engineer to support a Government customer by designing and implementing data infrastructure for an intelligence weapons system(s). This full-time onsite role is based in Stafford, VA, with a focus on building scalable, reliable data solutions through architecture, data modeling, and pipeline development.

What You’ll Do

Work with stakeholders to translate business and operations requirements into data models and data pipelines
Evaluate and help implement tools and processes that support data engineering initiatives
Monitor, troubleshoot, and optimize existing data workflows and systems
Document data models, pipelines, and processes to enable data, information, and knowledge sharing
Design a data strategy for integrating data from multiple sources with security and compliance considerations
Create conceptual, logical, and physical data models

Required Qualifications

Bachelor’s degree in computer science, data engineering, or a related field
5+ years of relevant experience
Advanced SQL skills, including building complex transformations and data models in a relational database
Python proficiency for data pipeline development, automation, or API integrations
Proficiency in data architecture and data modeling
Proficiency in data pipeline design, implementation, and operations
Familiarity with software configuration management tools and processes
Ability to establish and maintain effective team relationships
Strong written and verbal communication skills
Ability to work independently and collaborate effectively with cross-functional teams
U.S. citizenship with the ability to obtain and maintain a U.S. Government security clearance

Technologies

SQL
Python

Preferred Qualifications

Active TS/SCI clearance
Experience working with U.S. Government customers
Experience with Risk Management Framework
Experience in an Agile or DevOps environment
Experience with data observability, testing, and quality frameworks
Familiarity with Big Data processing tools such as Hadoop, Spark, NiFi, etc.
Experience designing, building, and maintaining scalable data pipelines
Experience implementing and promoting best practices for data governance, data quality, and observability
Experience designing, building, and implementing data pipelines and data models