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Remote Entry Level Data Engineering Jobs in Baltimore, MD

Mondo

Data Engineer

Baltimore, MD · Remote

$100K - $150K/yr

The schedule can be structured rotationally, such as 1-2 weeks onsite followed by 1-2 weeks remote ... This is a hands-on engineering role focused on designing, building, and maintaining secure ...

Fisher Organization

Entry-Level Remote Sales

Bowie, MD · Remote

Position: Entry-Level Manager - Leadership Development Track (Remote) If you're driven, coachable ... data and help your team strategize for success Organize and lead virtual training and onboarding ...

Fisher Organization

Entry-Level Remote Sales

Largo, MD · Remote

Position: Entry-Level Manager - Leadership Development Track (Remote) If you're driven, coachable ... data and help your team strategize for success Organize and lead virtual training and onboarding ...

Fisher Organization

Entry-Level Remote Sales

Towson, MD · Remote

Position: Entry-Level Manager - Leadership Development Track (Remote) If you're driven, coachable ... data and help your team strategize for success Organize and lead virtual training and onboarding ...

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All JobsData Engineering JobsRemote Entry Level Data Engineering JobsRemote Entry Level Data Engineering Jobs in Baltimore, MD

Remote Entry Level Data Engineering information

See Baltimore, MD salary details

$44.2K

$128.9K

$176.4K

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

As of Sep 13, 2026, the average yearly pay for remote entry level data engineering in Baltimore, MD is $128,891.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,800.00 and $136,600.00 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 are the most commonly searched types of Remote Data Engineering jobs in Baltimore, MD?

The most popular types of Remote Data Engineering jobs in Baltimore, MD are:

What are popular job titles related to Remote Entry Level Data Engineering jobs in Baltimore, MD?

For Remote Entry Level Data Engineering jobs in Baltimore, MD, the most frequently searched job titles are:

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

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

Remote Entry Level Data Engineering jobs near you
Infographic showing various Remote Entry Level Data Engineering job openings in Baltimore, MD as of September 2026, with employment types broken down into 3% Internship, 68% Full Time, 13% Part Time, 2% Temporary, and 14% Contract. Highlights an 100% Remote job distribution, with an average salary of $128,891 per year, or $62 per hour.

Data Engineer

Baltimore, MD • Remote

Mondo
See more jobs at Mondoexternal

$100K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago

Job description

Job Title: Data EngineerLocation-Type: Hybrid / Travel – Baltimore, MD (50–75% onsite)Work Hours: 40 Hours/WeekStart Date Is: ASAPDuration: PermanentCompensation Range: $100,000–$150,000/yearBenefits: Eligible for Medical, Dental, Vision, 401(k), PTO, Parental Leave, and Additional Company BenefitsMust be authorized to work in the U.S. This position is not eligible for sponsorship.

Travel Expectations:This position requires regular onsite work at the client office in Baltimore, with approximately 50–75% onsite presence. The schedule can be structured rotationally, such as 1–2 weeks onsite followed by 1–2 weeks remote. All required travel and accommodations are covered. Mileage is reimbursed for candidates who drive, while airfare and train travel are booked through the company's travel portal.

Job Description:Seeking an experienced Data Engineer to join a global technology organization as it expands its U.S. presence and supports a high-impact, federal-adjacent initiative in Baltimore.

This is a hands-on engineering role focused on designing, building, and maintaining secure, scalable data platforms and CI/CD pipelines within a complex client environment. The Data Engineer will work with large and varied datasets across legacy systems, APIs, telemetry/IoT sources, and modern cloud platforms while helping establish reliable infrastructure for analytics and future AI/ML capabilities.

The ideal candidate has strong production data engineering experience, thrives in client-facing environments, and can independently solve complex technical problems while collaborating with distributed teams and stakeholders.

Day-to-Day Responsibilities:

  • Design, build, and maintain scalable, production-grade data platforms and pipelines
  • Build and enhance CI/CD pipelines supporting reliable data engineering deployments
  • Develop ingestion and transformation pipelines across legacy systems, APIs, IoT/telemetry, relational databases, and other data sources
  • Design cloud-native architectures supporting batch, streaming, and near-real-time workloads
  • Build distributed and event-driven data processing solutions using Spark, Kafka, or equivalent technologies
  • Develop modern lakehouse and data warehouse architectures using technologies such as Databricks and dbt
  • Write clean, maintainable, production-quality code using Python and SQL
  • Implement automated testing, monitoring, observability, data-quality validation, lineage, and reliability standards
  • Build secure and governed data environments incorporating RBAC, encryption, auditability, and access controls
  • Support data infrastructure that enables analytics and future machine learning and AI use cases
  • Optimize data platforms for performance, scalability, reliability, and cost
  • Partner with engineers, data scientists, technical teams, and client stakeholders to translate requirements into scalable solutions
  • Troubleshoot complex production issues and take ownership of solutions through resolution
  • Contribute to architectural decisions and the long-term evolution of the data platform

Minimum Requirements:

  • 5 years of professional data engineering experience, including designing and operating production data platforms
  • Strong hands-on Python and SQL experience
  • Strong experience with Spark/PySpark and distributed data processing
  • Experience with Kafka, event streaming, or comparable streaming technologies
  • Experience designing and building modern data architectures such as lakehouses, data warehouses, data lakes, or distributed data platforms
  • Experience with Databricks, dbt, or comparable modern data technologies
  • Experience integrating multiple data sources including APIs, legacy systems, relational databases, and/or telemetry/IoT data
  • Experience with AWS, Azure, and/or GCP
  • Experience building or supporting CI/CD pipelines and production deployment processes
  • Understanding of Infrastructure as Code and cloud-native engineering practices
  • Experience building highly available, observable, production-grade data systems
  • Understanding of data governance, security, access controls, encryption, lineage, and auditability
  • Strong troubleshooting, systems-thinking, and problem-solving skills
  • Ability to independently own technical deliverables from design through production
  • Strong communication and stakeholder collaboration skills
  • Comfortable working directly with clients in complex, high-visibility environments
  • Ability to accommodate approximately 50–75% onsite work in Baltimore through a regular travel/onsite rotation

Preferred Qualifications:

  • Experience supporting government, public-sector, federal-adjacent, defense, infrastructure, healthcare, financial services, or another regulated environment
  • Experience with Databricks, dbt, Docker, Spark/PySpark, and Kafka
  • Experience designing secure data platforms subject to regulatory or compliance requirements
  • Familiarity with HIPAA, CJIS, FERPA, state privacy requirements, or similar security and privacy frameworks
  • Experience with Infrastructure as Code and automated cloud deployments
  • Experience supporting analytics, GIS, machine learning, or AI applications through robust data infrastructure
  • Experience with IoT, telemetry, infrastructure, or other complex real-world datasets
  • Experience working within globally distributed engineering teams
  • Previous consulting or client-facing engineering experience