United States

Developer Jobs in United States

4,403 jobs found

Include remote jobs

Today

Senior Full Stack Data Engineer

All IT Solutions Arlington, VA

Arlington, VA

Today

Contract Backend Developer Senior Big Data

Apply Now

Job Description

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

Role Overview

You will contribute to the architecture, design, and delivery of enterprise-grade solutions, including full-stack development and data platform engineering. The work includes building and maintaining distributed systems, optimizing performance, and collaborating with cross-functional stakeholders to meet engineering and business requirements.

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 with immediate and other development teams across programs to align on shared goals 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, contribute to engineering culture, and continuously develop technical skills while delivering reliable, high-quality software.
Build full-stack, data-intensive, analytics-driven applications that support business experimentation and decision-making.
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 data serving.
Build features for enterprise data onboarding, exchange, discovery, and consumption.
Write clean, maintainable, and efficient code with strong testing, code review, and continuous improvement practices.
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, stay current with technologies, and drive enhancements in quality, scalability, and developer productivity.

Required Qualifications

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), along with experience with CI/CD, testing, and optimization.
Experience with Data Governance, security, and utilizing reusable frameworks.
Experience as a full-stack Software Engineer, including exposure to building platforms using modern technologies such as 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 serving 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, including improving performance, scalability, and reliability across services and data-processing layers.
Strong collaboration and communication skills across cross-functional teams.
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

Location and Job Type

Location: Arlington, VA, USA (hybrid)
Job Type: contract

Apply

Apply Now: https://careers.allitsolutions.net/jobs/senior-full-stack-data-engineer-2026-47fbd561/apply

View full job page →

Today

AI/ML Data Engineer

Precise Software Solutions Incorporated Washington, DC

Washington, DC

Today

Full time Apache Airflow Artificial Intelligence Azure

Apply Now

Job Description

Precise Software Solutions Incorporated is hiring an AI/ML Data Engineer to help build and govern the data foundation behind 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 and support AI operations that are measurable, traceable, and built for responsible use.

What you’ll do

Design and maintain data ingestion, transformation, and processing pipelines (ETL/ELT) for AI training, evaluation, retrieval, and operations, including data migration and data cleansing.
Curate, validate, and version datasets while managing dataset inventories, metadata, lineage, provenance, and ingestion logs.
Implement automated data-quality checks for duplication, schema changes, completeness, and freshness, and maintain 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.
Evaluate 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 patterns for AI applications such as natural-language-to-SQL, including 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 all data in FedRAMP-authorized cloud regions with FIPS-validated encryption.
Support Responsible AI by preparing representative evaluation datasets, testing outputs for bias, accuracy, and hallucination, and documenting results to meet federal AI governance requirements.
Secure the AI data path across source datasets, embeddings, 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 using Airflow.
1+ year preparing data for Generative AI or machine learning, such as 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 (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.

View full job page →

Today

Data Engineer

Everforth ECS Fairfax, VA

Fairfax, VA

Today

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

Apply Now

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) in Fairfax, VA (onsite).

Responsibilities

Ingest, organize, store, manage, and securely transport structured and unstructured data within the SUNet environment
Perform approved data transfers between authorized systems, storage locations, enclaves, and users, following established security, data-handling, and customer requirements
Validate data transfers using methods such as manifests, file counts, checksums, metadata, and other verification approaches to confirm completeness and integrity
Maintain data inventories and documentation including metadata, storage locations, access information, and transfer records to improve visibility into available SUNet data holdings
Assist with on-premises and cloud data storage resource management, including capacity monitoring, dataset organization, storage requirement identification, and support for data lifecycle activities
Create, submit, coordinate, track, test, document, and close Change Requests related to data operations, system configurations, access needs, and customer-requested capabilities
Translate customer operational requirements 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 involving data access, permissions, file transfers, storage capacity, connectivity, and data availability; escalate more complex technical issues as appropriate
Build basic scripts and automation using Python, Bash, PowerShell, or similar tools to improve repetitive data management, validation, transfer, and reporting
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 including data migrations, capability demonstrations, testing events, and process-improvement initiatives for CDAO, government partners, and commercial AI/ML development teams

Requirements

Autonomous self-starter with a proven track record delivering complex data solutions independently and removing engineering blockers 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+

Salary

USD 100,000 - 115,000 per year

Benefits

Everforth ECS benefits

View full job page →

Today

Data Engineer

Space Dynamics Laboratory Stafford, VA

Stafford, VA

Today

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

Apply Now

Job Description

Space Dynamics Laboratory (SDL) is hiring a Data Engineer for a full-time onsite role supporting a Government customer in Stafford, VA. You will help design and implement the data infrastructure for an intelligence weapons system(s), delivering scalable, reliable data solutions through data modeling, pipeline development, and architecture work. The position is designed for engineers who value clear documentation, secure integration across sources, and strong collaboration with stakeholders.

Salary: $108,000 to $208,000 per year

Responsibilities

Collaborate with stakeholders to translate business and operations requirements into data models and data pipelines
Evaluate and implement tools and processes that support ongoing data engineering initiatives
Monitor, troubleshoot, and optimize existing data workflows and systems
Document data models, pipelines, and processes to support data, information, and knowledge sharing
Design a data strategy for integration of data from multiple sources, 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 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
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

Preferred Qualifications

Active TS/SCI clearance
Experience working with U.S. Government customers
Experience with Risk Management Framework
Experience working 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

Technologies

SQL
Python

View full job page →

Today

Lead Data Engineer

JPMorgan Chase Plano, TX

Plano, TX

Today

Full time Data Data Architecture Data Engineer

Apply Now

Job Description

JPMorgan Chase is hiring a Lead Data Engineer for the Consumer and Community Banking organization in Plano, TX. The role focuses on designing, building, and maintaining scalable batch and streaming data platforms that support business needs while meeting governance, performance, and regulatory expectations.

Key Responsibilities

Design, build, maintain, and optimize scalable batch and streaming data pipelines with performance, fault tolerance, and observability in mind.
Develop and operate workflow orchestration to schedule, monitor, and manage data movement and transformation workflows.
Convert complex business requirements into technical solutions aligned to data lake and data warehousing standards.
Use enterprise-authorized AI capabilities within the work environment to accelerate data pipeline design and documentation, including validating outputs and handling data according to sensitivity and security requirements.
Apply reuse-first, AI-assisted practices to strengthen SDLC-quality processes for data pipelines, including test generation and control validation, with traceability and auditability aligned 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, leading technical direction through standards, reviews, and knowledge sharing.
Stay current with advancements in AWS Data Lake, Snowflake Data Warehouse, and related technologies.
Perform advanced quantitative analysis on large datasets to identify business trends.
Manage data sharing and exchange, including ecosystem-specific features.

Required Qualifications

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, and Snowflake, as well as engines such as Spark, Flink, or Trino.
Experience applying Agile methodologies, including running ceremonies and prioritizing backlogs for continuous improvement.
Proficiency in SQL and experience with data pipeline and ETL tools.
Demonstrated ability to use enterprise-authorized AI capabilities within the work environment to support data engineering workflows, with strong validation habits and awareness of data sensitivity.
Ability to review and validate AI-assisted outputs (for example, 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.
Ability to design and implement large-scale data solutions in cloud environments.

Preferred Qualifications

Experience with data modeling in Erwin.
Experience with table formats such as Iceberg and Hudi.

Technology Focus

AWS Data Lake, Snowflake Data Warehouse
Redshift, BigQuery, Snowflake
Spark, Flink, Trino
SQL
Kafka, Pub/Sub
Erwin
Iceberg, Hudi

Role Location and Experience

Location: Plano, TX 75024 (onsite)

Minimum Experience: 5 years

View full job page →

Today

Senior Data Engineer

CMG Financial United States

United States

Today

$130k - $165k/yr Full time Senior Application Security Cdc

Apply Now

Job Description

CMG Financial is hiring a Senior Data Engineer (onsite in the United States) to build and operate a governed, Snowflake-based Enterprise Data Warehouse platform.

Responsibilities

Build and operate Snowflake ingestion from on-premises SQL Server systems (including BytePro) and from SaaS/vendor sources.
Use Fivetran, CDC / Change Tracking, Azure Data Factory, and vendor data shares for ingestion.
Develop and maintain Dagster (Dagster+) assets, schedules, sensors, and checks in Python.
Migrate remaining GitHub Actions-run and legacy SSIS jobs onto the orchestration platform.
Write and review dbt models, tests, seeds, and snapshots for Raw and Bronze layers.
Support Silver layer contracts built by domain teams.
Manage Snowflake as code with Pulumi (TypeScript), including databases, roles, grants, warehouses, service users, and policies.
Provision Azure resources with Terraform.
Deploy via GitHub Actions with reviewed, gated promotion across DEV, QA, UAT, and PROD.
Implement access controls using RBAC, tag-based column classification, and dynamic masking.
Create least-privilege service accounts with key-pair authentication and just-in-time elevation for sensitive data under GLBA, FCRA, and HMDA obligations.
Ensure approvals for sensitive access are recorded and auditable.
Build freshness, volume, and schema checks, including alerting and runbooks.
Detect and remediate silent failures such as stalled pipes, stale grants, and untagged objects before consumers are impacted.
Contribute to specs and ADRs, write clear PRs, and participate in rigorous code review.
Measure before asserting and maintain a verifiable trail for changes and outcomes.
Partner with Servicing, Lending, and Marketing data owners, plus Domo and BI developers during the SDW to EDW migration, including parallel-run reconciliation.
Mentor engineers and raise standards for testing, automation, and documentation.

Requirements

7+ years in data engineering, including 3+ years building production pipelines on a cloud data warehouse (Snowflake preferred).
Expert SQL and strong Python for pipeline and platform code with tests.
Hands-on dbt experience in production (modeling, testing, CI, and environments).
Experience with a modern orchestrator: Dagster, Airflow, or Prefect.
Hands-on managed ingestion or CDC: Fivetran or similar.
Infrastructure-as-code experience: Pulumi, Terraform, or similar; CI/CD with GitHub Actions or Azure DevOps.
Snowflake security depth: RBAC, masking, row-access policies, tags, service authentication, and cost-aware warehouse management.
Working knowledge of SQL Server source systems: CDC and Change Tracking, plus ability to read execution plans with a DBA team.
Experience handling regulated or sensitive data (e.g., PII and financial data) with auditable controls.
Clear written communication: ability to write specs, PR descriptions, and incident notes.

Technologies

Snowflake
SQL
Python
Fivetran
CDC / Change Tracking
Azure Data Factory
Dagster, Dagster+
dbt
Pulumi (TypeScript)
Terraform
GitHub Actions
SSIS
GLBA, FCRA, HMDA
SQL Server
Key-pair authentication
RBAC
Dynamic masking
Row-access policies
Tags
Azure DevOps
Airflow, Prefect
Azure resources
BytePro
Domo

Nice to Have

Mortgage, lending, or loan-servicing domain experience (origination, servicing, investor reporting).
Azure experience: Data Factory, ADLS, Key Vault, Entra ID groups, and SCIM provisioning.
Snowflake Iceberg / catalog-linked tables, secure data sharing, and reader accounts.
Data catalog and lineage tooling (OpenMetadata / DataHub or similar).
Experience migrating SSIS packages or legacy ETL onto modern tooling.
Domo or other BI platforms as downstream warehouse consumers.
Experience using AI coding assistants responsibly in a reviewed engineering workflow.
Streaming/event-driven data: Kafka (or Azure Event Hubs), change-data streams, and Snowflake streaming ingestion (Snowpipe Streaming) alongside batch pipelines.
Durable workflow orchestration and containers: Temporal (CMG adoption) and Kubernetes for running containerized services.
Data modeling experience with Inmon, Kimball, Medallion (Bronze / Silver / Gold), or Data Vault 2.0.
Experience with AI-Driven Development Lifecycle (AI-DLC) using a structured, human-governed, intent-to-deployment workflow with engineer-checked approvals.

How We Work

Changes land through reviewed pull requests, with production changes using approval gates.
Governance rules are documented as specs and ADRs and enforced in code and CI (access decisions driven by reviewed rules).
Prioritize measuring over assuming, fixing root causes over workarounds, and owning issues until closure.

Supervisory Responsibilities

Direct Reports: N/A

Physical and Environmental Conditions

Operates in an ADA compliant office environment using typical office equipment and computer-based work.
May involve partial stationary positions and moving throughout the day.
Overtime may be required to meet project deadlines.

Compensation

Annual Salary: $130,000 - $165,000
Actual compensation determined based on relevant data engineering experience, IT background, mortgage industry depth, technical skills, education, and other job-related qualifications.

View full job page →

Today

Data Engineer 4 (Manager, IC)

Information Technology Senior Management Forum Chicago, IL

Chicago, IL

Today

$179k - $205k/yr Full time Backend Developer Manager Big Data

Apply Now

Job Description

The Data Engineer 4 (Manager, IC) role is an onsite opportunity in Chicago, IL with the Information Technology Senior Management Forum. In this position, you will help build and deliver cloud-first data solutions, while also leading engineering work across Agile teams. The work focuses on scalable data pipelines, reusable engineering patterns, and security and compliance practices.

As a senior engineering contributor, you will work at the intersection of data engineering and distributed systems, using modern tooling and data platforms to support robust experiences for millions of Americans. The role is designed for strong technical ownership, including designing and delivering solutions with minimal support.

What you’ll do

Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies
Influence a team of developers, data analysts, and data scientists with experience spanning machine learning, distributed microservices, lakehouse architecture, and full-stack systems
Use Python and Spark with open-source relational and NoSQL databases and cloud data warehousing platforms including Databricks and Snowflake
Experiment with and learn new technologies, participate in internal and external technology communities, and mentor others in the data community
Work with product managers and software engineers to deliver robust cloud-first data solutions
Independently design, build, and deliver cloud data solutions and applications with little or no support from supervisors or managers
Architect and enforce common data engineering design patterns to improve code quality, maintainability, and reusability
Design and build data pipelines and platforms with an emphasis on scalability, resilience, and operational efficiency
Implement data security standards, including encryption at rest, encryption at transit, and fine-grained access control to meet data privacy regulations
Serve as a data engineering ambassador by communicating technical concepts and data outcomes clearly to internal and external stakeholders

Required qualifications

Bachelor’s Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 4 years of experience in application development (internship experience does not apply)
At least 2 years of experience in distributed data
At least 2 years of experience with SQL
At least 2 years of experience with one programming language: Python, Java, or Scala
At least 2 years of experience in data pipeline design and development
At least 1 year of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems

Technologies you’ll work with

Python, Spark
Databricks, Snowflake
SQL, relational databases, NoSQL databases
Agile
Machine learning
Distributed microservices, lakehouse architecture
Encryption at rest, encryption at transit, fine-grained access control

Preferred qualifications

7+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java
4+ years of hands-on experience designing, deploying, and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
4+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
4+ years of experience designing, implementing, and operating real-time or streaming data pipelines
2+ years of experience working on data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster)
4+ years of experience working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
4+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
2+ years of experience working in an Agile development environment
2+ years of experience developing user-centric reusable data products

Compensation and location

Location: Chicago, IL (onsite)
Salary: USD 179,400 to 204,700 per year

Immigration authorization

Capital One will not sponsor a new applicant for employment authorization or provide immigration-related support for this position (including H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, O-1, and other work authorization forms requiring employer immigration support).