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Worldwide Remote Data Jobs

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1d ago

Data Engineer - Analytics Products

DC Public Charter School Board Remote 🌍 Remote

Remote

1d ago

$84k - $103k/yr Full time Analytics Business Intelligence Data Analysis

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Job Description

Data Engineer on the Analytics Products team at the DC Public Charter School Board will work remotely to design and maintain data pipelines, data warehouse models, orchestration workflows, and Data Marts that support reporting, accountability calculations, Enterprise Intelligence, and public analytics. This is a remote position with an effective start date in July 2026, and a salary range of USD 83,520 to 103,172 per year.

Responsibilities

Design, build, and sustain ETL/ELT pipelines using Airflow, SQL, and Python to support analytical workflows, reporting products, and accountability calculations.
Maintain and improve the Data Warehouse architecture, including data models, schemas, dependencies, and documentation.
Support the development and reliability of the Data Mart, ensuring governed, non-PII data are structured for reporting (star schemas), analysis, and Enterprise Intelligence use cases.
Develop and manage Airflow orchestration workflows that support recurring data submissions, validation processes, report production, and downstream analytics products.
Implement schema validation and transformation logic to ensure submitted and processed data conform to standards and Data Mart models.
Monitor and resolve Airflow failures, pipeline errors, and data quality issues in collaboration with Analytics Engineers and Product Managers.
Support accountability-related data infrastructure, including ASPIRE, state assessment reporting, school performance reporting, and potential concurrent accountability calculation frameworks.
Manage cloud-based data infrastructure using AWS RDS, S3, IAM, and related services.
Contribute to a CI/CD environment by writing tests, performing peer code reviews, and ensuring reliable deployment of data pipelines and infrastructure changes.
Collaborate with Analytics Engineers and Product Managers to translate user stories, reporting needs, and policy requirements into reliable data models and automated workflows.
Support Data Governance by maintaining data quality, privacy, transparency, and auditability across systems.
Contribute to the Data Team Handbook and participate in Agile rituals, including sprint planning, reviews, and retrospectives, to improve team processes.

Requirements

At least five years of professional experience in data engineering, analytics engineering, software engineering, database development, or a closely related technical role, with substantial SQL and Python experience in production or recurring workflows.
Experience building and maintaining ETL/ELT pipelines that move data from source systems into databases, data warehouses, Data Marts, reporting layers, or analytics products, including handling structured data and implementing validation steps.
Experience designing, maintaining, or improving data models for databases, warehouses, or analytics, with understanding of table grain, keys, relationships, dependencies, versioning, and downstream reporting usage.
Experience creating governed, report-ready datasets, views, tables, or semantic models for reporting and analysis; familiarity with dimensional modeling, star schemas, and non-PII reporting is helpful.
Experience developing, maintaining, or troubleshooting scheduled data workflows using Airflow or similar orchestration tools; ability to monitor recurring workflows, diagnose failures, and implement durable fixes.
Experience writing and optimizing SQL for production data systems; knowledge of query performance, joins, indexing, migrations, data volume, and impacts on reporting products.
Experience with cloud infrastructure and DevOps for data, including AWS services such as RDS, S3, IAM, CloudWatch, Lambda, or ECS; familiarity with Git, CI/CD, Docker, and infrastructure-as-code practices is helpful.
Experience implementing data quality, privacy, lineage, documentation, access controls, or auditability in data pipelines or warehouse models; experience with education or public-sector data is helpful.
Experience writing maintainable, tested, and documented code with version control; comfortable with peer reviews and documenting assumptions for long-term maintainability.
Experience collaborating with analysts, product managers, program staff, or other non-engineering partners to translate reporting or accountability needs into reliable data infrastructure.
Commitment to the DC PCSB mission, REDI principles, and building transparent, reliable, and equitable data systems for public education oversight.

Technologies

Airflow
SQL
Python
AWS RDS
AWS S3
AWS IAM
AWS CloudWatch
AWS Lambda
AWS ECS
Git
CI/CD
Docker
Infrastructure as Code practices

Benefits

A comprehensive benefits plan that covers 100 percent of the employee's insurance premium.
Generous telecommuting policy.
Public Service Loan Forgiveness (PSLF) eligibility consideration for qualifying government or not-for-profit employment; details at studentaid.gov.
A non-negotiation policy for compensation to promote fair practices within the organization.

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1d ago

Data Engineer, Product Analytics

Meta Remote 🌍 Remote

Remote

1d ago

$177k - $247k/yr Full time Analytics Data Analytics Data Architecture

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Job Description

What you’ll gain

Meta supports remote work and offers a competitive compensation package, with a yearly salary between USD 177,000 and USD 247,000. You will shape product development across Meta’s apps by collaborating with software engineers, data scientists, and product managers, turning data into clear, actionable insights. The role centers on building scalable data architectures, advanced visualizations, and robust data models that inform decisions across teams, while fostering growth through mentorship and cross-functional collaboration.

Responsibilities

Lead the data architecture for multiple large-scale projects, weighing design options and operational costs to optimize value.
Develop and contribute to data logging frameworks, coordinating with data infrastructure to triage and resolve issues.
Work with engineers, product managers, and data scientists to capture data needs and present key insights through meaningful visualizations.
Define and manage service level agreements for data sets under ownership.
Design and implement security models aligned with privacy requirements, ensure safeguards are followed, address data quality, and evolve governance within your domain.
Create and deploy sophisticated data models and visualizations that support diverse use cases across products or domains.
Address complex data integration challenges using effective ETL patterns, frameworks, and query techniques, sourcing from structured and unstructured data.
Maintain production processes and optimize code with advanced algorithmic approaches.
Improve pipelines, dashboards, frameworks, and systems to streamline the development of data artifacts.
Influence product and cross-functional teams by identifying data opportunities with measurable impact.
Mentor team members through actionable feedback to support ongoing growth within the group.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical experience.
7+ years of experience focused on working with data, including roles such as data analyst, data scientist, data engineer, or similar.
7+ years with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, or other).

Technologies

SQL, Python, C++, C#, Scala, ETL

Benefits

Bonus
Equity
Benefits

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2d ago

Senior Data Engineer

Sgn Global Technologies Remote 🌍 Remote

Remote

2d ago

$50 - $55/hr Full time Senior Azure Machine Learning Azure Synapse Analytics

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Job Description

Senior Data Engineer role at Sgn Global Technologies, a remote W2 position focused on building and maintaining SQL databases, ELT/ETL pipelines, and data processing using Python, PySpark/Polars, Azure Synapse Analytics, and Azure Machine Learning.

Responsibilities

Maintain SQL databases and perform advanced SQL and T‑SQL operations to ensure data integrity and performance.
Design, implement, and sustain ELT/ETL pipelines within cloud-based analytics environments.
Collaborate with Azure Synapse Analytics and Azure Machine Learning in the modern data stack; DP-203 certification or equivalent is preferred.
Manipulate and transform data using Python, with Pandas proficiency required.
Work with PySpark and/or Polars to process large-scale datasets as needed.

Requirements

Bachelor’s degree in Data Engineering, Computer Science, Data Science, Machine Learning, Mathematics, or a related field, or 5+ years of relevant applied work experience.
5+ years hands-on experience maintaining SQL databases and performing advanced SQL and T‑SQL operations.
5+ years hands-on experience designing, implementing, and maintaining ELT/ETL pipelines in cloud-based data analytics environments.
3+ years hands-on experience with Azure Synapse Analytics and Azure Machine Learning using the modern data stack; DP-203 (or equivalent) certification is preferred.
Data manipulation using Python with Pandas required.
Experience with PySpark and/or Polars is preferred.

Technologies

SQL
T‑SQL
Azure Synapse Analytics
Azure Machine Learning
Python
Pandas
PySpark
Polars

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2d ago

Data Scientist/Palantir Data Engineer

ITS Consulting, Inc. Remote 🌍 Remote

Remote

2d ago

$120k - $160k/yr Full time Analytics Anomaly Detection Big Data

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Job Description

Two seasoned data professionals to support Navy ERP plus SAP data migration by delivering advanced analytics, data quality initiatives, and Palantir Foundry driven migration capabilities.

Responsibilities

Architect, implement, and maintain Palantir Foundry based data pipelines and analytics applications.
Build scalable data profiling to evaluate SAP ERP data quality and readiness for migration.
Implement automated anomaly detection to identify data inconsistencies, duplicates, and integrity gaps.
Develop cleansing, matching, and standardization workflows to improve migration quality.
Create reconciliation controls to validate migrated data for completeness and accuracy.
Construct migration dashboards, KPIs, and reporting that deliver real-time migration metrics to stakeholders.
Collaborate with SAP, ERP, and business teams to define migration requirements and data quality rules.
Optimize data pipelines for performance, scalability, and reliability.
Support data governance, metadata management, and lineage within Palantir Foundry.
Assist with testing, validation, and deployment of migration analytics solutions.
Document technical designs, data models, and operational procedures.

Requirements

Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or related technical field.
3+ years of experience in data engineering, data science, analytics, or enterprise data management.
Hands-on experience with Palantir Foundry.
Experience working with SAP ERP data, particularly in migration or modernization initiatives.
Strong SQL skills and experience developing scalable ETL/ELT pipelines.
Proficiency in Python, Spark, or similar data engineering technologies.
Active U.S. Secret Security Clearance (ability to maintain clearance throughout employment).
U.S. Citizenship required; dual citizenship not permitted.
Data profiling, data quality assessment, data cleansing, and deduplication skills.
Data reconciliation capabilities.
Knowledge of enterprise data modeling and metadata management.
Experience developing dashboards and data visualizations.
Strong analytical, troubleshooting, and problem-solving abilities.
Excellent written and verbal communication skills.

Technologies

Palantir Foundry
SAP ERP / SAP S/4HANA
SQL
Python
Apache Spark
ETL/ELT Development
Data Quality Frameworks
Data Profiling
Data Governance
Data Reconciliation
Data Matching & Deduplication
Dashboard Development
Git
REST APIs
AWS, Azure, Google Cloud

Benefits

401(k)
401(k) matching
Flexible schedule
Health insurance
Paid time off
Retirement plan
Vision insurance

What You'll Deliver

Scalable Palantir Foundry based data engineering solutions
Automated data profiling and anomaly detection capabilities
Data cleansing and matching workflows
Migration reconciliation controls
Executive dashboards and migration metrics
High quality, trusted data that accelerates Navy ERP+ SAP migration success

Job Type

Full-time

Pay

$120,000 - $160,000 per year

Application Question(s)

Do you have a US Citizenship without having a dual citizenship elsewhere?

Education

Bachelor's degree (Preferred)

Work Location

Remote

Preferred Qualifications

Experience supporting Department of Defense or U.S. Navy programs
Familiarity with Navy ERP or large federal ERP modernization efforts
Experience with SAP S/4HANA migration projects
Knowledge of Master Data Management concepts
Experience with cloud-based data platforms (AWS, Azure, or Google Cloud)
Familiarity with Agile software development methodologies
Active Secret or higher security clearance or ability to obtain one

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2d ago

AI Engineer

Stride, Inc. Remote 🌍 Remote

Remote

2d ago

$66k - $145k/yr Full time Python Ai Workflows Artificial Intelligence

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Job Description

Stride, Inc. is seeking an AI Engineer to lead the end-to-end development and deployment of AI-powered data products built on large-scale machine learning. This remote role focuses on model design, evaluation, and production rollout, aligning with Stride coding best practices and business objectives. The position requires a Bachelor’s degree in a quantitative field and at least six years of related experience.

Responsibilities

Applies expertise in applied AI, model, API, and pipeline creation, as well as the presentation of data to see beyond the numbers and understand how our users interact with our core products;
Provide strategic influence with Product and Engineering teams to solve problems and identify trends and opportunities;
Collaborates with IT managers, data stewards, and data engineers to ensure that AI workflows are efficiently provisioned with high-quality data and follow best practices in security, privacy, and scalability;
Informs, influences, and supports product direction by translating business needs into innovative yet practical AI solutions that drive measurable outcomes;
Ensures that AI output is measurable, documented, reproducible, and actively monitored for performance drift. Implements practices for continuous improvement and retraining as needed;
Manages the development of AI resources by gathering requirements, organizing data sources, and supporting the integration of AI models into product throughout the product lifecycle;
Holds a key thought leadership role on teams responsible for defining and evaluating strategies to improve academic outcomes, leveraging applied AI expertise to inform decisions;
Ensures that Stride’s AI capabilities support schools and school services teams, facilitating adoption and use of actionable data to deliver improved outcomes;
Identifies and defines new opportunities to leverage AI across different business units and functions in support of Stride’s mission, vision, and long-term strategy;
Demonstrates genuine enthusiasm for education and the Stride experience, inspiring colleagues and stakeholders to harness AI for meaningful impact on student success;

Requirements

Bachelor’s degree in Computer Science, Math, Physics, Engineering, or related quantitative field AND Six (6) years’ related experience; OR Equivalent combination of education and experience
Hands-on experience with modern ML libraries (e.g., Python-based frameworks such as TensorFlow, PyTorch, scikit-learn) and understanding of statistical principles.
Proficiency with AWS, Azure, Docker, Kubernetes, and Terraform to build scalable, secure, and high-performing environments.
Ability to design, implement, and maintain robust ML pipelines, including version control, containerization (Docker, Kubernetes), and CI/CD processes.
Ensures model integrity and reliability, validating outputs to deliver precise and actionable insights.
High attention to detail and high level of accuracy.
Strong analytical skills.
Strong customer service orientation.
Professional integrity necessary to maintain confidentiality.
Strong planning skills and ability to manage multiple projects simultaneously.
Excellent verbal, and written communication skills.
Ability to complete assigned duties within critical deadlines.
Ability to work independently and in a team environment.
Proficient with Microsoft Office (Word, Excel, PowerPoint, and Outlook).
Proficiency with modern reporting platforms and tools.
Ability to grasp complex platform concepts and business models, in a digital context.
Ability to clear required background check

Technologies

Python
TensorFlow
PyTorch
scikit-learn
AWS
Azure
Docker
Kubernetes
Terraform
Microsoft Office (Word, Excel, PowerPoint, Outlook)

Benefits

Health benefits
Retirement contributions
Paid time off
Bonus

Work Environment

This is a home-based position

Compensation & Benefits

Salary range: USD 66,380 - 145,000 per year. Stride, Inc. considers a person’s education, experience, and qualifications, as well as the position’s work location, expected quality and quantity of work, required travel (if any), external market and internal value when determining a new employee’s salary level. Salaries will differ based on these factors, the position’s level and expected contribution, and the employee’s benefits elections. Offers will typically be in the bottom half of the range. We anticipate the salary range to be $66,379.

Job Type

Regular

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3d ago

Senior Machine Learning Engineer

Placement Force Remote 🌍 Remote

Remote

3d ago

$160k - $260k/yr Full time Senior Artificial Intelligence Data Pipeline

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Job Description

Placement Force seeks a Senior Machine Learning Engineer to own the complete lifecycle of a production large language model, from initial training and fine-tuning to scalable deployment and rigorous evaluation.

Responsibilities

Design and run pretraining, continued pretraining, and fine-tuning workflows, including supervised fine-tuning, alignment methods such as DPO and RLHF, as well as LoRA/QLoRA and full-parameter training, all tied to well-defined, measurable goals.
Own data pipeline decisions that materially affect model quality, covering data curation, deduplication, mixture weighting, and contamination checks against evaluation datasets.
Execute and interpret distributed training across multiple GPUs and nodes using FSDP, DeepSpeed, or Megatron-style parallelism, diagnosing scale-specific issues such as loss spikes, stragglers, and checkpoint corruption.
Make and justify tradeoffs between model size, training cost, and downstream performance.
Deploy trained models to production with quantization, batching strategies, KV-cache management, and serving framework selection (for example vLLM, TensorRT-LLM, TGI), accompanied by explicit latency, throughput, and cost targets.
Design for LLM serving failure modes, including tail latency under load, graceful degradation, prompt injection risk, and safe fallback behavior.
Develop the operational capabilities around production models, including monitoring, alerting, and rollback paths, applying the same rigor as for other critical services.
Create and maintain evaluation harnesses that go beyond published benchmarks, incorporating task-specific evaluation sets aligned to real product use cases.
Establish human evaluation protocols where automated metrics fall short, and determine the appropriate contexts for each approach.
Own regression detection to catch quality drops caused by new checkpoints, prompt template changes, or serving optimizations before they impact users.
Contribute to safety and robustness evaluation, including measures of hallucination, adversarial testing, and behavior under distribution shift, as an integral part of the release process.

Requirements

More than four years of applied ML engineering experience, with at least two years directly working on large language models in production.
Proven production deployment experience shipping models that served live traffic, with demonstrated awareness of latency, cost, and quality tradeoffs.
Strong software engineering fundamentals.
Fluency with the modern LLM tooling landscape, including training frameworks, serving frameworks, and evaluation tooling.
Comfort with ambiguity and the ability to define what constitutes acceptable model behavior in the absence of established benchmarks.

Technologies

FSDP
DeepSpeed
Megatron-style parallelism
vLLM
TensorRT-LLM
TGI

About the Role

This role involves owning the full lifecycle of a production large language model, spanning training and fine-tuning through deployment at scale and rigorous evaluation of what actually ships. It requires fluency across research, engineering, and production, because the most challenging problems emerge at the intersections of these domains.

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3d ago

Machine Learning Engineer

Lyntris Remote 🌍 Remote

Remote

3d ago

Contract Artificial Intelligence Data Pipeline Data Processing

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Job Description

A remote contract role at Lyntris to build NLP pipelines and LLM powered document understanding to transform engineering documentation into structured, machine-actionable knowledge.

Responsibilities

Design, implement, and maintain NLP pipelines for technical and structured document understanding, including information extraction, summarization, semantic search, and question answering.
Build and optimize LLM powered applications using transformer-based models, including fine-tuning, prompt engineering, and retrieval augmented generation (RAG) architectures.
Process and analyze complex technical corpora such as engineering manuals, specifications, technical reports, drawings, tables, and figures.
Develop methods to convert unstructured and semi-structured documents into structured, machine-actionable knowledge for downstream applications.
Implement scalable machine learning solutions using Python and modern frameworks such as PyTorch and Hugging Face.
Evaluate model performance, improve accuracy, and optimize inference pipelines for production environments.
Collaborate with cross-functional teams including software engineers, data scientists, and subject matter experts to define requirements and deliver AI-enabled document intelligence solutions.
Performs other duties as assigned.

Requirements

Bachelor's degree in Computer Science, Data Science, AI/Machine Learning, or a related technical field (or equivalent practical experience).
2-4 years of experience building NLP pipelines for technical or structured document understanding, including extraction, summarization, semantic search, and question answering.
Hands-on experience with large language models and transformer architectures (BERT and successors), including fine-tuning, prompt engineering, pipeline orchestration, and retrieval augmented generation (RAG).
Experience processing complex technical documentation such as engineering manuals, specifications, technical artifacts, tables, and figures.
Strong proficiency in Python and modern ML frameworks, including PyTorch and Hugging Face Transformers.
Demonstrated experience converting unstructured text into structured, machine-actionable knowledge.
Currently holds an active U.S. national security clearance or be able to receive and maintain one.

Technologies

Python
PyTorch
Hugging Face Transformers
BERT

Benefits

Paid Time Off
Paid Company Holidays
Medical, Dental & Vision Insurance
Optional HSA and FSA
Base and Voluntary Life Insurance
Short Term & Long-Term Disability Insurance
401k Matching
Employee Assistance Program

Physical Requirements

Prolonged periods sitting at a desk and working on a computer.
Must be able to lift up to 15 pounds at times.

Clearance Requirements

Some positions will require access to U.S. National Security information. Positions that require this access will be required to receive and maintain a U.S. government personnel security clearance (PCL). In order to qualify for this position, the candidate must be a US citizen and either currently possess this National Security eligibility or be able to complete the investigation application process with a favorable determination and maintain that eligibility throughout their employment.

EEOC & Know Your Rights

Lyntris companies are Equal Opportunity Employers. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, status as a protected veteran or any other status protected by applicable federal, state, and local law. We ensure that all employment decisions, including hiring, promotion, compensation, and other terms and conditions of employment, are based on merit, qualifications, and business needs.

Preferred Qualifications (Not Required)

Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field.
Experience deploying and maintaining production-scale NLP or LLM applications.
Familiarity with vector databases, embedding models, and semantic retrieval systems.
Experience with document parsing, OCR, layout-aware models, or multimodal document understanding.
Experience working with engineering, manufacturing, aerospace, defense, or other highly technical datasets.
Knowledge of MLOps practices, model monitoring, CI/CD pipelines, and cloud-based AI infrastructure.
Active-duty military experience.