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Remote Entry Level Data Engineering Jobs in Delmont, PA

JLL

Data Collection Specialist II

Pittsburgh, PA · Remote

Bachelor's degree (BA/BS) in engineering, construction management, sciences, IT, or related field a ... Remote -Boston, MA, Chicago, IL, Cleveland, OH, Dallas, TX, Indianapolis, IN, JERSEY CITY, NJ, Las ...

GAI Consultants

EIT - Traffic Engineer

Homestead, PA · On-site +1

GAI Consultants, Inc is seeking an Entry Level (1-3 years experience) "Traffic Engineer- in ... Hybrid or remote work is available with residency required in the Commonwealth of PA. A successful ...

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All JobsData Engineering JobsRemote Entry Level Data Engineering JobsRemote Entry Level Data Engineering Jobs in Delmont, PA

Remote Entry Level Data Engineering information

See Delmont, PA salary details

$39.6K

$115.4K

$157.9K

How much do remote entry level data engineering jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote entry level data engineering in Delmont, PA is $115,358.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,800.00 and $122,300.00 per year, depending on experience, location, and employer.

What is a remote entry level data engineer?

A remote entry level data engineer is a professional who works from a location outside of a traditional office setting to help design, build, and maintain the data infrastructure and pipelines needed for organizations to collect and analyze data. These roles are suitable for individuals new to the field, often requiring foundational knowledge in programming, databases, and data processing tools. Entry level data engineers typically work under the guidance of more experienced team members and focus on tasks such as data cleaning, basic ETL (extract, transform, load) processes, and supporting data integration projects. Working remotely allows for flexibility and collaboration using digital communication tools.

What are the key skills and qualifications needed to thrive as a remote entry level data engineer?

To thrive as a Remote Entry Level Data Engineer, you need a foundational understanding of databases, data modeling, and programming languages such as Python or SQL, often supported by a relevant degree or coursework. Familiarity with cloud platforms (like AWS or Azure), ETL tools, and version control systems (such as Git) is typically required. Strong problem-solving skills, attention to detail, and effective virtual communication are essential soft skills for remote collaboration and troubleshooting. These skills ensure efficient data pipeline development, data integrity, and productive teamwork in distributed engineering environments.

What are some common challenges faced by remote entry level data engineers, and how can they be addressed?

Remote entry level data engineers often face challenges such as limited hands-on mentorship, understanding complex data pipelines, and collaborating across different time zones. To overcome these, it's helpful to proactively communicate with your team, seek feedback regularly, and make use of virtual collaboration tools. Participating in team meetings, asking questions, and accessing available documentation will help you build confidence and stay aligned with project goals.

What is the difference between Remote Entry Level Data Engineering vs Remote Junior Data Analyst?

AspectRemote Entry Level Data EngineeringRemote Junior Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; basic SQL and programming skillsBachelor's in related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, cloud platforms, data pipelinesReporting, data interpretation, dashboards
Industry UsageTech, finance, healthcare, e-commerceMarketing, retail, finance, healthcare

Remote Entry Level Data Engineering focuses on building data pipelines and managing data infrastructure, requiring technical skills like SQL and programming. Remote Junior Data Analysts interpret data, create reports, and support decision-making. While both roles involve working with data remotely, data engineers handle data infrastructure, whereas data analysts focus on analyzing and visualizing data to provide insights.

Can I work remotely as a remote entry level data engineer?

Yes, many entry-level data engineering roles are available as remote positions, especially with the rise of cloud-based tools like AWS, Azure, and GCP. These jobs typically require knowledge of SQL, Python, and data pipeline tools, and often offer flexible schedules for remote work.

What job categories do people searching Remote Entry Level Data Engineering jobs in Delmont, PA look for?

The top searched job categories for Remote Entry Level Data Engineering jobs in Delmont, PA are:

What cities near Delmont, PA are hiring for Remote Entry Level Data Engineering jobs?

Cities near Delmont, PA with the most Remote Entry Level Data Engineering job openings:

Remote Entry Level Data Engineering jobs near you
Infographic showing various Remote Entry Level Data Engineering job openings in Delmont, PA as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 19% Part Time, 1% Temporary, and 6% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $115,358 per year, or $55.5 per hour.

Machine Learning Engineer, Data Mining

Motional

Pittsburgh, PA • On-site, Remote

$144K - $192K/yr

Full-time

Re-posted 29 days ago

Job description

Mission Summary:
At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.
As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from Motional's driving data, working at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

  • Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). Focus on implementing supervised and self-supervised learning approaches to improve data search and retrieval.
  • Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines. Assist in applying standard optimization techniques (e.g., batch inference, quantization) to ensure models run efficiently in production environments.
  • Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows to identify critical driving scenarios.
  • Monitor Production Performance: Help build and maintain dashboards to monitor model health, data drift, and system performance. Identify regressions and assist in the operational support of our data mining services.
  • Learn and Apply Best Practices: Follow software engineering standards (version control, CI/CD, unit testing) for ML code. Participate in code reviews and contribute to technical documentation.
  • Collaborate Across Teams: Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable, scalable engineering solutions.

What We're Looking For (Must-Haves):

  • BS or MS in Computer Science, Machine Learning, or a related field.
  • Hands-on experience with PyTorch (preferred) or TensorFlow/JAX. You should be comfortable training models and evaluating them using standard metrics.
  • Strong proficiency in Python with the ability to write clean, modular, and well-documented code.
  • Working knowledge of version control, unit testing, and basic software design patterns.
  • Experience working with large datasets, including proficiency in SQL and data libraries like Pandas and NumPy.
  • A solid grasp of the full ML lifecycle, from data cleaning and feature engineering to validation and deployment basics.
  • A proactive learner who thrives on constructive feedback and is eager to grow within a high-stakes engineering environment.

Bonus Points (Nice-to-Haves):

  • MS/PhD in Computer Science, Machine Learning, or related field.
  • Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
  • Background in autonomous driving, robotics, or real-time decision-making systems.
  • Familiarity with multimodal learning, sensor fusion, or embodied AI.
  • Experience building active learning loops, using the model to find the data that breaks the model.
  • Experience with ML-based data mining, active learning, or contrastive learning.
  • Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
  • Publication in top-tier conferences (e.g., ICCV, CVPR, ECCV)

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.

Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

Salary Range
$144,000—$192,000 USD

Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more.

Our journey is always people first.

We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.

Higher purpose, greater impact.

We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do.

Scale up, not starting up.

Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.

Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.

Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.