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133 jobs found

Today

Senior Data Engineer - Technology

Neptune Technology Group Inc. Duluth, GA

Duluth, GA

Today

Full time Senior Amazon Web Services AWS

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Job Description

The Senior Data Engineer role at Neptune Technology Group Inc. focuses on owning and modernizing the data pipeline architecture, migrating ETL workloads from Redshift stored procedures and legacy SSIS to scalable, maintainable pipelines built with AWS Glue and S3, and guiding the shift toward near real-time analytics using stream processing technologies such as Apache Flink and ClickHouse.

Responsibilities

Design and implement modern ETL and ELT pipelines leveraging AWS Glue, S3, and related services to replace legacy stored procedures and SSIS jobs.
Architect data transformation workflows that are testable, version-controlled, and observable.
Optimize and maintain the Redshift data warehouse, focusing on materialized views, query performance, and cost efficiency.
Advance the platform from batch ETL to near real-time stream processing by evaluating and deploying technologies such as Apache Flink, ClickHouse, Kafka, Kinesis, or equivalent.
Design pipelines capable of supporting both near real-time and batch workloads during the transition.
Collaborate with product and analytics teams to ensure data models support reporting, AI/ML initiatives, and customer-facing features.
Establish patterns and best practices for pipeline development adopted by the broader team.
Participate in production support and incident response for data infrastructure.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, with a minimum of five years in data engineering roles.
Extensive experience with AWS Glue (PySpark/Python), S3, and Redshift.
Proven track record migrating ETL workloads from legacy tools such as SSIS or stored procedures to modern cloud-native pipelines.
Strong SQL skills with best practices and SQL linting, particularly in Redshift or other columnar/MPP databases.
Experience with or strong interest in stream processing frameworks (Flink, Spark Streaming, Kafka Streams, or similar).
Familiarity with data pipeline orchestration, monitoring, and error handling patterns.
Experience with infrastructure-as-code and CI/CD for data pipelines.

Technologies

Python
PySpark
SQL
AWS Glue
S3
Redshift
SSIS
Apache Flink
ClickHouse
Kafka
Kinesis
Apache Spark Streaming
Kafka Streams
Aurora MySQL
DynamoDB
Apache Druid
dbt
Airflow
Step Functions
MQTT

Location

Onsite in either Tallassee, Alabama or Duluth, Georgia. Travel to manufacturing or customer locations may be required up to 20% of the time when necessary.

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Today

Machine Learning Engineer - Document Digitization (LLMs)-Vice President

JPMorganChase Jersey City, NJ

Jersey City, NJ

Today

$164k - $260k/yr Full time Ai Ml Amazon Eks Artificial Intelligence

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Job Description

Senior Vice President level Machine Learning Engineer at JPMorgan Chase, focusing on designing, building, and deploying AI powered document digitization solutions with LLMs in Jersey City, NJ (onsite).

Responsibilities

Lead the design, development, and integration of AI powered document digitization solutions to extract information from diverse document types.
Oversee the end-to-end AI/ML lifecycle: training, validation, deployment, monitoring, and production grade continuous improvement.
Apply generative AI and large language models to automate and optimize document workflows.
Build and maintain scalable digitization pipelines using Python, AI frameworks, and cloud technologies.
Provision and manage cloud resources with infrastructure as code tools (Terraform) and AWS services such as SageMaker and Bedrock.
Ensure scalability, reliability, security, and governance compliance of AI/ML solutions.
Collaborate with cross functional teams to reimagine legacy document processing using generative AI and LLMs.
Develop dashboards and reporting tools to monitor digitization accuracy, workflow efficiency, and business impact.
Mentor junior engineers and promote best practices in AI/ML, software engineering, and testing.
Conduct model validation, human in the loop reviews, and implement continuous improvement strategies for digitization accuracy.
Contribute to communities of practice and explore new and emerging technologies.

Requirements

Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or a related field with relevant industry experience.
Strong proficiency in Python for building production grade AI services and data/document pipelines.
Strong working proficiency in Java, including API and microservice development with Spring Boot; familiarity with front end technologies (React.js, AngularJS) is a plus.
Hands-on experience delivering LLM powered or GenAI applications in production (document understanding, retrieval augmented generation, workflow automation) including evaluation, observability, guardrails, and continuous improvement.
Experience with MLOps / LLMOps practices in production environments (CI/CD, automated testing, deployment strategies, monitoring, incident response).
Working knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning) focused on integrating models and services into scalable systems.
Experience with AWS and cloud native delivery, including SageMaker and/or Bedrock, containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
Familiarity with NoSQL / search / graph technologies (MongoDB Atlas, Elasticsearch/OpenSearch, Neo4j) and their use in document search and knowledge retrieval.
Experience with agentic coding approaches, autonomous/assisted code agents, orchestration patterns, and tool-use/agent frameworks to accelerate digitization workflows.
Strong understanding of SDLC, CI/CD, resiliency, and security practices; proven problem solving, communication, and collaboration skills.
Demonstrated ability to accelerate development using AI technologies while maintaining engineering rigor (testing, code quality, governance).

Technologies

Python
Terraform
AWS SageMaker
AWS Bedrock
Docker
Kubernetes
Amazon EKS
Java
Spring Boot
React.js
AngularJS
TensorFlow
PyTorch
Scikit-learn
PyTorch Lightning
MongoDB Atlas
Elasticsearch/OpenSearch
Neo4j
LLMs

Benefits

Equity/stock-based compensation
Competitive base salary
Commission-based pay and/or discretionary incentive compensation
Comprehensive health care coverage
On-site health and wellness centers
Retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching

About JPMorganChase

JPMorganChase is a long standing financial services institution serving consumers, small businesses, and large organizations worldwide under the J.P. Morgan and Chase brands. With a history spanning more than 200 years, the firm leads in investment banking, consumer and small business banking, commercial banking, payments processing, and asset management.

About the Team

Corporate Functions teams cover a broad range of areas from finance and risk to human resources and marketing. These professional groups play a key role in enabling business success for clients, customers, and employees across the organization.

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Today

Data Scientist

Agile Defense Tampa, FL

Tampa, FL

Today

Full time Analytics Artificial Intelligence Big Data

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Job Description

Agile Defense is seeking a Data Scientist to design, develop, and deploy scalable AI-enabled data solutions for the DoD CDAO ADA IR program. The role operates within a multidisciplinary team in secure containerized environments, turning complex data into decision-ready insights for mission-critical applications.

You will collaborate across product management, software engineering, platform teams, and mission stakeholders to transform raw data into actionable analytics and decision-support tools.

Responsibilities

Support the design, development, and deployment of scalable, AI-powered data solutions within the DoD CDAO ADA IR program.
Join a multidisciplinary team that integrates advanced analytics, machine learning, and engineering practices into mission-critical environments across Combatant Commands.
Design and implement data pipelines, preprocessing workflows, feature engineering strategies, and ML services inside secure, containerized environments.
Collaborate with product managers, full-stack developers, platform engineers, and mission stakeholders to convert raw data into meaningful insights and decision-support tools.

Requirements

4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
Proficiency in Python, SQL, and distributed data frameworks such as Spark, Databricks, or PySpark.

Technologies

Databricks
Palantir
AWS
Python
SQL
Spark
PySpark
scikit-learn
TensorFlow
XGBoost
MLflow
Tableau
Plotly
Matplotlib
Palantir Foundry

Requisition

1590

Location

Falls Church, VA
Ft. Meade, MD
Stuttgart, Baden-Württemberg, Germany
Tampa, FL
Honolulu, HI (Camp H.M. Smith)
Colorado Springs, CO
Doral, FL
Omaha, NE
Scott Air Force Base, IL

Clearance

Top Secret with the ability to obtain an SCI. Must have clearance to start.

Education and Background

Bachelor's degree plus 3 years of recent specialized experience
Associate's degree plus 7 years of recent specialized experience
Major certification plus 7 years of recent specialized experience
11 years of recent specialized experience

Preferred Skills

Experience developing ML models from training to deployment using industry-standard tools and libraries (eg, scikit-learn, TensorFlow, XGBoost, MLflow).
Familiarity with MLOps, API development, and secure cloud-based environments (AWS, Azure, Palantir Foundry).
Strong understanding of data validation, model testing, and performance evaluation techniques.
Experience with data visualization and storytelling using Tableau, Plotly, or Matplotlib.
Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.

Working Conditions

Requires work onsite in a SCIF.

Core Values

Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do.
Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated.
Honest - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support.
Humble - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task.
Hungry - Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges.
Hustle - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success.

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Today

Data Scientist

Agile Defense Washington, DC

Washington, DC

Today

$130k - $155k/yr Full time Analytics Artificial Intelligence Big Data

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Job Description

Agile Defense offers a mission driven environment where data science and engineering converge to deliver AI enabled data solutions for Department of Defense programs. You will join a multidisciplinary team executing advanced analytics, machine learning, and decision support tools in mission critical settings. This onsite role in Washington, DC offers a competitive salary of USD 130,000 to 155,000 per year, plus comprehensive health, retirement, and learning and development opportunities. The position is based in a SCIF at the Pentagon, reflecting a secure, collaborative work culture.

What you will do

Contribute to the design, development, and operational deployment of scalable AI enabled data solutions within the DoD CDAO ADA IR program.
Shape and deploy data pipelines, preprocessing workflows, feature engineering strategies, and ML services inside secure, containerized environments.
Collaborate with product managers, full stack developers, platform engineers, and mission stakeholders to turn raw data into meaningful insights and decision support tools.
Work as part of a multidisciplinary team that integrates advanced analytics, machine learning, and engineering practices in mission critical environments across Combatant Commands.

Requirements

4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
Proficiency in Python, SQL, and distributed data frameworks such as Spark, Databricks, and PySpark.
Experience moving ML models from training to deployment using industry standard tools and libraries (eg, scikit-learn, TensorFlow, XGBoost, MLflow).

Technologies

Python
SQL
Spark
Databricks
PySpark
scikit-learn
TensorFlow
XGBoost
MLflow
AWS
Azure
Palantir Foundry
Tableau
Plotly
Matplotlib

Benefits

Health Insurance
Life Insurance
Paid Time Off
Holiday Pay
Short-term Disability
Long-term Disability
Retirement
Learning and Development opportunities
Other optional benefit elections

Education and Background

A bachelor's degree plus 3 years of recent specialized experience, OR an associate's degree plus 7 years of recent specialized experience, OR a major certification plus 7 years of recent specialized experience, OR 11 years of recent specialized experience.

Experience

Minimum 3 years of relevant work experience, with the exact requirement varying by educational path.

Working conditions

Onsite in a SCIF at the Pentagon, Washington, DC.

Our core values

Happy - Be Infectious. Happiness multiplies and fosters a positive, connected environment that amplifies motivation and satisfaction.
Helpful - Be Supportive. Collaboration thrives when teammates are genuinely helpful, driving collective success.
Honest - Be Trustworthy. Transparency and ethical conduct guide all actions in complex domains.
Humble - Be Grounded. Humility supports mutual respect and openness to learning and collaboration.
Hungry - Be Eager. A strong drive for excellence fuels innovation and continuous improvement.
Hustle - Be Driven. A relentless work ethic propels the mission forward and ensures dependable results.

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Today

Lead Data Engineer / Data Architect

Glint Tech Solutions LLC Charlotte, NC

Charlotte, NC

Today

Full time Azure Data Factory Azure Data Lake Storage Azure Synapse Analytics

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Job Description

Glint Tech Solutions LLC is steering an enterprise modernization program for a major US retail eCommerce platform, where a robust data architecture underpins fast, reliable customer experiences. The Lead Data Engineer / Data Architect will shape the enterprise data strategy and design scalable platforms through re-architecture, database migrations, and cloud-native microservices migration. This onsite role is based in Charlotte, NC.

Responsibilities

Design and own enterprise data architecture supporting high-volume retail eCommerce operations
Build and maintain ETL/ELT pipelines using Azure Data Factory, Synapse Analytics, and Databricks/pySpark
Design conceptual, logical, and physical data models for efficient data storage and retrieval
Implement data warehousing solutions including dimensional modeling, star schemas, Data Mesh, Delta Lakehouse, and Data Vault
Lead database migrations and microservices migrations to unified cloud-native solutions
Integrate data from databases, APIs, and external providers via API integration and message queuing
Embed metadata and governance processes into cloud-based data platforms
Lead and mentor cross-functional engineering teams while driving technical strategy and stakeholder communications

Requirements

8+ years of overall experience with at least 1 year in an architect-level role
3+ years of hands-on Azure Data Factory and Azure Synapse Analytics experience
Deep Microsoft Azure expertise including Data Lake Storage, Databricks, pySpark, Cosmos DB, and PostgreSQL
Strong SQL proficiency for complex queries, transformations, and cloud performance tuning
Experience with Azure MI, Cosmos DB, Analysis Services, and Informix
Proficiency in Python and Python-based ETL tools
Shell scripting experience (Bash, Unix, or Windows)
Proven ability to lead teams, define technical strategy, and communicate across organizational levels

Technologies

Azure Data Factory
Azure Synapse Analytics
Databricks
pySpark
Data Lake Storage
Cosmos DB
PostgreSQL
SQL
Python
Bash
Unix
Windows
Azure MI
Analysis Services
Informix
Elasticsearch
Docker
Kubernetes
Delta Lake
Delta Lakehouse
Data Mesh
Data Vault

Company overview

Glint Tech Solutions is a women-owned global staffing and IT recruiting firm connecting top technical talent with leading enterprise clients across the United States and Canada.

Nice-to-have skills

Elasticsearch experience
Docker and Kubernetes familiarity
Performance tuning and pipeline optimization expertise
Azure, Databricks, or relevant cloud certifications

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Today

Staff Data Engineer

Okta Chicago, IL

Chicago, IL

Today

$174k - $239k/yr Full time Senior Apache Airflow Cloud

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Job Description

Okta is seeking a Staff Data Engineer to join the Auth0 Data Engineering Team in Chicago, IL on a hybrid schedule. This role leads the architectural evolution of the core data platform, starting with FEDRamp compliance, and drives scalable, secure designs across multiple teams. The position offers a salary range of USD 174,000 to 238,700 per year, with benefits that emphasize well-being, social impact, and talent development within a collaborative culture.

Benefits

Supporting Your Well-Being
Driving Social Impact
Developing Talent and Fostering Connection + Community

The Auth0 Data Engineering Team

Pipeline team — sits near the Platform team and data producers, responsible for efficient data ingestion and rapid access to unmodeled data
Warehouse team — aligns with business teams and data consumers, modeling data in the data warehouse to abstract complexity and simplify analysis, reporting, and decision-making
Interface team — builds and manages connections between the data platform and external systems to ensure consistent and reliable data access

Responsibilities

Spearhead the evolution of the core data platform, shaping the long-term architectural roadmap
Set the technical direction for large-scale platform improvements, balancing visionary goals with incremental delivery
Collaborate with engineers and leaders across data, platform, and security to deliver a cohesive and secure architecture
Create architectural artifacts such as design documents, threat models, and technical specifications to drive clarity and alignment on complex initiatives
Serve as a technical mentor and multiplier for the Data Engineering team, elevating performance through guidance, code reviews, and sharing best practices
Build foundational components of the new architecture, validating designs with hands-on coding and serving as a model for other engineers

Requirements

A passion for building secure, reliable, and scalable data systems
8+ years of software development experience, with at least 5+ years in a data engineering or data platform role
Proven experience designing and delivering large-scale, cross-functional technical projects
Extensive experience architecting and deploying data infrastructure in a cloud environment, with AWS strongly preferred
Deep architectural knowledge of the modern data stack, including data warehouses (Snowflake), transformation tools (dbt), and orchestrators (Airflow)
Strong proficiency in Python and SQL, with a high bar for code quality and system design
Excellent communication skills, with the ability to create clarity and drive decisions on complex technical topics
Ability to deal with ambiguity, define a path forward, and lead others to successful outcomes

Technologies

Technologies: Snowflake, dbt, Airflow, Python, SQL, AWS, Terraform, Kubernetes

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Today

Principal Data Scientist Insights & Intelligence

Northrop Grumman Remote 🌍 Remote

Remote

Today

$114k - $171k/yr Full time Analytics Artificial Intelligence Big Data

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Job Description

Northrop Grumman's Insights & Intelligence division is recruiting a Principal Data Scientist to drive analytical programs and deliver production-grade data science solutions that inform engineers, program managers, and leaders. This remote-hybrid role emphasizes translating business challenges into rigorous analytics and strategic insights across the organization.

Responsibilities

Collaborate with engineers, program managers, and subject-matter experts to scope problems, frame the right analytical questions, and translate business needs into robust data science strategies
Break down complex problems with critical thinking, evaluate data quality and relevance, challenge assumptions, and design methods that address the business objective
Develop statistical models, machine learning solutions, and analytical frameworks that yield actionable insights and guide operational decisions
Build user-friendly, production-ready ML/AI applications (for example Streamlit, Dash) and analytic artifacts that deliver insights to teams across the enterprise
Write production-grade Python code and assemble analytics pipelines on cloud platforms (AWS, Databricks) to support scalable, reproducible workflows
Deliver insights through executive recommendations, analytical reports, interactive dashboards, and direct discussions with business leaders
Own the technical quality and business impact of your work by making thoughtful methodological choices, validating approaches, and standing behind recommendations
Stay current on analytical methods, statistical techniques, and domain-specific best practices to continually improve quality and impact

Requirements

At least five years of hands-on experience in data science, data analysis, or related professional roles
Strong proficiency with Python, SQL, and Git
Solid understanding of statistical methods, machine learning algorithms, and selecting appropriate analytical techniques
Experience developing and deploying machine learning models in production environments
Proven ability to translate complex business problems into rigorous analytical frameworks
Demonstrated problem-solving and critical-thinking skills to tackle complex analytical challenges
Excellent communication skills with the ability to present actionable recommendations to non-technical stakeholders
Proven ownership and accountability for technical decisions and project outcomes

Technologies

Python
SQL
Git
Streamlit
Dash
AWS
Databricks
PySpark
Docker

Benefits

Health insurance coverage
Life and disability insurance
Savings plan
Company paid holidays
Paid time off for vacation and/or personal matters
Overtime eligibility
Shift differential eligibility
Discretionary bonus
Annual bonuses
Long-term incentives

Relocation assistance

No relocation assistance available

Clearance required for start

None

Clearance type

None

Travel

Yes, 10% of the time

Work arrangement

This is a hybrid/remote role. The majority of the team is based in the Northern Virginia area, but the organization operates primarily remotely and values flexibility. The standard schedule is a 9/80, with nine-hour days Monday through Thursday and every other Friday off.

Salary

USD 113,900.00 - 170,900.00 per year

Location

Remote (hybrid)

Preferred qualifications

Experience with AWS and Databricks for data processing and model development
Experience with PySpark for large-scale data transformation and analytics
Proven experience building and deploying web-based visualization or decision-support tools (Streamlit, Dash)
Knowledge of MLOps concepts and best practices for deploying models to production
Understanding of containerization and cloud-based deployment
Familiarity with advanced analytical techniques such as causal inference, experimental design, time series forecasting, optimization, or Bayesian methods
Domain experience in program management, business management, operations research, earned value management, or financial forecasting
Background in consulting or client-facing technical roles where ambiguous business problems were translated into technical solutions