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Senior Full Stack Data Engineer

All IT Solutions Arlington, VA

Arlington, VA

Today

Contract Backend Developer Senior Big Data

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Job Description

All IT Solutions is supporting a client engagement for a Senior Full Stack Data Engineer role based in Arlington, VA, USA (hybrid). This position focuses on scalable data platforms and data-intensive, analytics-driven applications spanning application, service, and data-processing layers.

The work combines full-stack development with data engineering to deliver enterprise-grade solutions, including performance tuning, operational support, and collaboration across teams and stakeholders across global time zones.

Key Responsibilities

Contribute to the architecture, design, and development of scalable data platforms and data-intensive applications.
Develop across application, service, and data-processing layers using technologies including Java/Spring Boot, React, TypeScript, Databricks, Spark, Hadoop, and related platforms.
Collaborate with your immediate team and other development teams to align on shared goals, support cross-cutting initiatives, and deliver cohesive enterprise-grade outcomes.
Participate in design and code reviews, contribute to engineering best practices, and help drive operational excellence.
Work effectively across global time zones, support a strong engineering culture, and continuously build technical skills while delivering reliable, high-quality software.
Build innovative products that help businesses unlock more value from their data.
Develop full-stack, data-intensive, analytics-driven applications that support business experimentation and decision-making for large organizations.
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 data processing, transformation, and serving.
Build features supporting enterprise data onboarding, exchange, discovery, and consumption.
Contribute to architecture and system design with cross-functional teams to deliver scalable, high-quality solutions aligned with best practices.
Write clean, maintainable, and efficient code using testing, code reviews, and continuous improvement practices.
Identify and resolve performance bottlenecks across services, APIs, data-processing workloads, and user experience.
Partner 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, stay current with technologies, and drive improvements 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 in Databricks/Hadoop using PySpark/SQL
Java (backend) plus React/TypeScript (frontend), with CI/CD, testing, and optimization experience
Experience related to Data Governance and security, including utilizing reusable frameworks
Experience as a full-stack Software Engineer, including exposure to building platforms with Java/Spring Boot, TypeScript, and React
Experience building large-scale data platforms, distributed systems, and enterprise integration solutions 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 a focus on improving performance, scalability, and reliability across services and data-processing layers
Strong collaboration and communication skills for cross-functional teamwork
Curiosity, self-motivation, and willingness to learn 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

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Job Type: Contract

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AI/ML Data Engineer

Precise Software Solutions Incorporated Washington, DC

Washington, DC

Today

Full time Apache Airflow Artificial Intelligence Azure

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Job Description

Precise Software Solutions Incorporated is seeking an AI/ML Data Engineer to help build and govern the data foundation that powers secure, AI-enabled applications for the U.S. Government. In this onsite role in Washington, DC, you will own AI-ready datasets end-to-end, from ingestion and quality controls to privacy protection, lineage, and retrieval-quality measurement, while supporting measurable and operationally secure AI.

Responsibilities

Design and maintain data ingestion, transformation, and processing pipelines (ETL/ELT) for AI training, evaluation, retrieval, and operations, including data migration and cleansing support.
Curate, validate, and version datasets; maintain 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 and embedding schema documentation, and responses to Government data calls.
Build secure structured-data access for AI applications (for example, 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 with FIPS-validated encryption.
Support Responsible AI practices by preparing representative evaluation datasets, testing AI outputs for bias, accuracy, and hallucination, and documenting results to meet federal AI governance requirements.
Secure the AI data path, from source datasets and embeddings to prompts and logs, and support AI risk testing such as data poisoning.

Requirements

Bachelor’s degree in Computer Science, Engineering, Mathematics, Information Systems, or a related field, plus 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; experience with data processing frameworks such as pandas and Spark and workflow orchestration tools such as Airflow.
1+ year of experience 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 on-site at Government offices.
Must be able to obtain and maintain a Public Trust background investigation.

Technologies

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 (for example, pgvector, OpenSearch).
Experience with MLOps tooling, including model and dataset versioning, feature stores, or model registries.
Generative AI, LLM security, or data certification (for example, Databricks Generative AI Engineer, Snowflake SnowPro, AWS, Microsoft Azure, or Google Cloud).
An active Public Trust or prior federal background investigation.

Location: Washington, DC (onsite)
Experience: 5+ years
Education: Bachelor’s degree

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Today

Business Analytics Engineer

Cushman & Wakefield Creve Coeur, MO

Creve Coeur, MO

Today

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

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Job Description

Business Analytics Engineer role focused on building analytics, reporting, automation, and geospatial solutions that support real estate portfolio decision-making.

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 convert business requirements into reusable technical solutions.
Support portfolio planning and workplace strategy through insight generation and visualization for occupancy analysis, location intelligence, and operational decision-making.
Find opportunities to improve efficiency through automation, standardization, and adoption of emerging technologies, including AI-enabled tools.
Assist in the ongoing evolution of PAG analytics, reporting, geospatial, and technology capabilities.
Build dashboarding and reporting solutions using Power BI, Looker, Tableau, or similar platforms for portfolio performance and operational efficiency.
Create and maintain data pipelines, transformation processes, and data models supporting analytics and reporting solutions (Databricks experience 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, and workplace planning.
Identify and automate repetitive reporting, data preparation, and operational workflows.
Leverage AI-enabled tools to improve productivity, accelerate development, and enhance analytics capabilities.
Understand business needs and priorities through collaboration with account teams, business stakeholders, and clients.
Communicate technical concepts clearly to both technical and non-technical audiences.
Support user adoption through training, documentation, and continuous improvement activities.

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 for business stakeholders.
Experience with Power BI, Tableau, Looker, or similar business intelligence platforms.
Experience building and maintaining data pipelines in modern cloud analytics platforms; 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 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 in consulting, professional services, or client-facing environments.
Experience leveraging AI-enabled tools such as Microsoft Copilot, Claude, Gemini, ChatGPT, or similar technologies.
Experience across 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

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

Success in This Role Looks Like

Stakeholders trust the data, reporting, and analytics solutions used to support 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.

Location: Creve Coeur, MO (onsite) • Salary: USD 106,250 - 125,000 per yearly • Experience: 3 years • Education: Bachelor's degree in Data Analytics, Information Systems, Computer Science, Business, Geography/GIS, Engineering, Mathem

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Today

Data Engineer

Everforth ECS Fairfax, VA

Fairfax, VA

Today

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

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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). The role emphasizes secure handling of structured and unstructured data, including ingestion, storage, movement, validation, documentation, and user access for authorized government and commercial stakeholders.

Key Responsibilities

Support ingestion, organization, storage, management, and secure transport of structured and unstructured data within the SUNet environment.
Perform approved data transfers between authorized systems, storage locations, enclaves, and users in alignment with established security, data-handling, and customer requirements.
Validate data transfers using manifests, file counts, checksums, metadata, or other verification methods to maintain completeness and integrity.
Maintain data inventories, metadata, storage locations, access information, transfer records, and supporting documentation to improve visibility into available SUNet data holdings.
Assist with on-premises and cloud-based data storage resource management, including capacity monitoring, dataset organization, identifying storage needs, and supporting data lifecycle activities.
Generate, submit, coordinate, track, test, document, and close Change Requests related to data operations, system configurations, access requirements, and customer-requested capabilities.
Support customer requirement implementation by converting operational needs into data-management actions, technical tasks, configuration changes, or process improvements under the guidance of senior technical personnel.
Assist with onboarding new government and commercial users, data sources, and development teams by coordinating data access, identifying required datasets, and supporting approved data-transfer workflows.
Troubleshoot routine issues involving data access, permissions, file transfers, storage capacity, connectivity, and data availability, escalating more complex technical issues when appropriate.
Develop basic scripts and automation using Python, Bash, PowerShell, or similar tools to improve repetitive data-management, validation, transfer, and reporting activities.
Develop and maintain technical documentation, including standard operating procedures, data-flow diagrams, data inventories, transfer procedures, troubleshooting guides, Change Request documentation, and operational runbooks.
Support special projects such as data migrations, capability demonstrations, testing events, and process-improvement initiatives to meet CDAO and partner needs, including government partners and commercial AI/ML development teams.

Requirements

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

Technologies

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

Compensation and Location

Location: Fairfax, VA (onsite)
Salary: USD 100,000 - 115,000 per year

Benefits

Everforth ECS provides benefits.

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Today

Mid-Level Data Engineer

Everforth ECS Remote 🌍 Remote

Remote

Today

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

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Job Description

Everforth ECS is hiring a Mid-Level Data Engineer to support a high-priority DHS OCIO data analytics and business intelligence platform. This position is remote and focuses on day-to-day operations of data-dependent systems, building reliable data pipelines, and working within a cross-functional agile environment.

Key Responsibilities

Lead development across the data pipeline, including storing, managing, and provisioning data to data consumers.
Collaborate with data scientists, data architects, and federal stakeholders to deploy models into production.
Develop and maintain code to support the performance and reliability of data extraction and processing.
Enable continuous automation for data ingest.
Promote technical excellence by applying lean-agile engineering principles and practices, including API-first design, simple design, continuous integration, version control, and automated testing.
Work with program management and engineering teams to implement and document complex, evolving requirements.
Contribute to a culture focused on customer service excellence, innovation, collaboration, and teamwork.
Partner with a cross-functional group that may include user experience researchers and designers, product managers, engineers, and other functional specialists.

Required Qualifications

Must be a US Citizen.
Must be able to obtain 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, such as PostgreSQL.
Ability to work comfortably in version control systems, such as Git.

Technologies

AWS
Redshift
Python
R
SQL
SAS
PostgreSQL
Git
ETL

Location

Remote (remote)

Compensation

USD 130,000 - 140,000 per year

Benefits

Benefits - Everforth ECS

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Today

Data Engineer

Space Dynamics Laboratory Stafford, VA

Stafford, VA

Today

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

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Job Description

Space Dynamics Laboratory (SDL) is hiring a Data Engineer to support a Government customer with the design and implementation of data infrastructure for an intelligence weapons system(s). This is a full-time onsite role in Stafford, VA, focused on building scalable and reliable data solutions across data modeling, pipelines, and data architecture.

Responsibilities

Collaborate with stakeholders to convert 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 data strategy for integrating data from multiple sources while ensuring security and compliance
Create conceptual, logical, and physical data models

Requirements

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
Proficiency in Python for data pipeline development, automation, or API integrations
Proficiency with data architecture and data modeling
Proficiency with data pipeline design, implementation, and operations
Familiarity with software configuration management tools and processes
Ability to establish and maintain effective team relationships
Effective written and verbal communication skills
Ability to work independently and collaborate effectively with cross-functional teams
Must be a U.S. citizen and able 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 (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

Compensation and Location

Location: Stafford, VA (onsite).
Salary: USD 108,000 - 208,000 per year.

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Today

Lead Data Engineer

JPMorgan Chase Plano, TX

Plano, TX

Today

Full time Data Data Architecture Data Engineer

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Job Description

JPMorgan Chase is hiring a Lead Data Engineer for its Consumer and Community Banking organization in Plano, TX (onsite). In this role, you will design, develop, and maintain data pipelines and architectures that support scalable, secure, and efficient analytics across the business while aligning to operational and regulatory expectations.

You will lead technical delivery across batch and streaming systems, strengthen data governance and stewardship, and partner with teams to turn complex requirements into standards-compliant data lake and warehouse implementations.

What you’ll do

Design, build, maintain, and optimize scalable batch and streaming data pipelines with performance, fault tolerance, and observability.
Develop and operate workflow orchestration to schedule, monitor, and manage data movement and transformations.
Convert complex business needs into technical solutions that meet data lake and data warehousing standards.
Use enterprise-authorized AI capabilities within the work environment to accelerate pipeline and design analysis and documentation, while validating outputs and applying data sensitivity and security handling requirements.
Apply reuse-first, AI-assisted practices to improve SDLC-quality routines for data pipelines, including test generation and control validation, with traceability/auditability and alignment to resiliency and security expectations.
Build and maintain governance processes for data modeling, cataloging, ownership, and access control.
Provide mentorship and training on data publication best practices, and lead the team’s technical direction through standards, reviews, and knowledge sharing.
Stay current on advancements in AWS Data Lake, Snowflake, and related technologies.
Perform advanced quantitative analysis of large datasets to identify business trends.
Manage data sharing, exchange, and ecosystem-specific features.

Requirements

Bachelor’s degree in Computer Science, Information Technology, or a related field.
5+ years of data engineering experience with deep expertise in AWS, data lake, and Snowflake.
Hands-on experience with modern data lake and warehousing technologies, including Redshift, BigQuery, Snowflake, and engines such as Spark, Flink, or Trino.
Experience applying Agile methodologies, running ceremonies, and prioritizing backlogs for continuous improvement.
Proficiency in SQL and experience with data pipeline/ETL tools.
Demonstrated experience using enterprise-authorized AI capabilities to support data engineering workflows, with strong validation habits and awareness of data sensitivity.
Ability to review and validate AI-assisted outputs (such as query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements.
Experience designing and building streaming pipelines using Kafka, Pub/Sub, or similar messaging systems.
Experience with large-scale distributed data processing and performance tuning.
Capability to design and implement large-scale data solutions in cloud environments.