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Remote Data Engineer Jobs in Trenton, NJ (NOW HIRING)

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ...

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ...

Remote Duration 4-6 months Advanced SAS programming (Base, Macro, SQL) in clinical trials with RBQM/RBM experience, hands-on clinical data analysis (KRIs/QTLs), EDC data integration (RAVE preferred ...

Remote Duration 4-6 months Advanced SAS programming (Base, Macro, SQL) in clinical trials with RBQM/RBM experience, hands-on clinical data analysis (KRIs/QTLs), EDC data integration (RAVE preferred ...

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

Remote Job Summary We are seeking an experienced AI/ML Engineer to build and deploy secure ... Build robust ETL and data pipelines , metadata catalogs, and ontologies for AI training and ...

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Remote Data Engineer information

See Trenton, NJ salary details

$44.6K

$130.1K

$178K

How much do remote data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for remote data engineer in Trenton, NJ is $130,074.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,800.00 and $137,900.00 per year, depending on experience, location, and employer.

What is a remote data engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

What does a remote data engineer do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

What are the key skills and qualifications needed to thrive as a remote data engineer, and why are they important?

To thrive as a Remote Data Engineer, you need strong programming skills in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

What is the difference between Remote Data Engineer vs Remote Data Analyst?

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

Are remote data engineers still in demand?

Remote data engineers are currently in high demand due to the increasing reliance on data-driven decision making and cloud-based data platforms. Skills in SQL, Python, cloud services, and data pipeline tools are highly sought after, and many organizations continue to hire for remote roles to access a broader talent pool.

Can a remote data engineer work remotely?

Yes, remote data engineers can work remotely, as the role primarily involves managing data pipelines, databases, and cloud-based tools that can be accessed from anywhere with an internet connection. Many companies offer remote positions for data engineers, often requiring skills in SQL, Python, cloud platforms, and data architecture. However, some roles may require occasional on-site presence or specific certifications depending on the employer's policies.

What are the most commonly searched types of Data Engineer jobs in Trenton, NJ?

The most popular types of Data Engineer jobs in Trenton, NJ are:

What job categories do people searching Remote Data Engineer jobs in Trenton, NJ look for?

The top searched job categories for Remote Data Engineer jobs in Trenton, NJ are:

What cities near Trenton, NJ are hiring for Remote Data Engineer jobs?

Cities near Trenton, NJ with the most Remote Data Engineer job openings:

Infographic showing various Remote Data Engineer job openings in Trenton, NJ as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $130,074 per year, or $62.5 per hour.

Senior Manager, Data Operations

Medical Guardian

Philadelphia, PA • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago


Job description

About Medical Guardian: 

Medical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. With 14 consecutive years on the Inc. 5000 list of Fastest Growing Companies, we are redefining what it means to age confidently and independently. 

We support over 625,000 members nationwide with life-saving emergency response systems and remote patient monitoring solutions. Trusted by families, healthcare providers, and care managers, our work is powered by a culture of innovation, compassion, and purpose. 

General Responsibilities: 

The Senior Manager of Data Operations leads the organization's Data Operations function and ensures that enterprise data services, reporting capabilities, and operational processes are reliable, governed, secure, and aligned with business priorities. The role establishes the operating model, service expectations, and continuous-improvement direction and advises technology and business leadership. 

The Senior Manager will lead a team of individual contributors supporting the organization's current data warehouse, dbt models, business reporting, data quality processes, and operational analytics. As the company's data architecture and platforms evolve, the Senior Manager will partner closely with Data Engineering to maintain continuity, quality, documentation, and effective business support. 

The Senior Manager will serve as the primary operational bridge between business stakeholders and Data Engineering, establishing priorities, service levels, governance practices, and measures of success for enterprise data services. Protecting PHI and other sensitive member information remains a critical responsibility. 

To advance these objectives, the Senior Manager of Data Operations will lead the people, processes, controls, and partnerships needed to deliver reliable and trusted data services. Key responsibilities include: 

  • Lead, coach, and develop Data Operations individual contributors while establishing the team's operating model, service roadmap, priorities, standards, measures of success, and continuous-improvement direction. 
  • Own portfolio intake, capacity planning, prioritization, coordination, and status communication for business reporting, dashboard, and operational data requests, balancing business value, risk, urgency, and available resources. 
  • Oversee the operational management of the organization's data warehouse and dbt-based modeling processes, ensuring reliable delivery, documentation, quality, and support. 
  • Serve as the senior operational representative for Data Operations and business-service requirements in data architecture and platform discussions, influencing priorities and operating decisions with Data Engineering and Enterprise Architecture. 
  • Partner with Data Engineering to establish clear operational and technical ownership for data products, models, pipelines, documentation, quality controls, lineage, and ongoing support. 
  • Translate business needs into clear requirements, priorities, acceptance criteria, and operational expectations for Data Engineering and other technology partners. 
  • Establish and monitor service-level objectives for critical reports, dashboards, datasets, and operational data processes, including availability, freshness, completeness, accuracy, and delivery timeliness. 
  • Coordinate data incident response, stakeholder communication, root-cause analysis, corrective actions, and follow-through for data-service failures and recurring quality issues. 
  • Maintain an inventory of critical data products, business owners, technical owners, dependencies, authoritative sources, lineage, and service expectations. 
  • Partner with business stakeholders to define and govern key performance indicators, semantic definitions, and trusted reporting sources, reducing duplicate or conflicting metrics and data models. 
  • Oversee business reporting and visualization practices so complex information is communicated clearly and consistently to executive and functional stakeholders, including Finance, Marketing, Operations, and other business areas. 
  • Coordinate business acceptance testing and validation for new or materially changed data products, reports, dashboards, and operational processes. 
  • Develop and manage data governance and operating procedures in partnership with Security, Privacy, Compliance, Data Engineering, and Enterprise Architecture, including data quality, access, documentation, lineage, retention, and secure handling of PHI and other sensitive data. 
  • Provide executive-level reporting on Data Operations performance, business impact, risks, capacity, and priorities, including reliability, data quality, incident trends, delivery time, backlog health, and adoption of trusted reporting assets. 
  • Manage relationships with external data vendors, partners, and consultants as needed. 

Technical Requirements 

This role requires sufficient technical depth across the data stack to manage operational performance, evaluate risks and outcomes, and partner effectively with engineering teams. 

  • Strong understanding of modern data warehousing and lakehouse concepts, dbt, dimensional data modeling, semantic layers, and business intelligence delivery. 
  • Ability to assess data-service health, identify operational and data-quality risks, understand technical trade-offs, and work effectively with data engineers and architects. 
  • Practical SQL proficiency sufficient to investigate data issues, validate results, understand data models, and evaluate the quality and usability of delivered data products. 
  • Experience establishing automated and operational data-quality controls, including monitoring, alerting, issue triage, ownership, remediation tracking, and reporting. 
  • Experience applying service-management practices to data products, including service levels, incident management, problem management, change coordination, root-cause analysis, and continuous improvement. 
  • Strong knowledge of data governance, metadata, lineage, access control, privacy, retention, and secure data-handling practices in a regulated environment. 
  • Working knowledge of Git-based version control, CI/CD, automated testing, orchestration, and observability concepts as they apply to analytics engineering and data pipelines. 
  • Experience with reporting and visualization platforms such as Power BI or Tableau, including the governance and adoption of curated dashboards and reporting assets. 
  • Experience with cloud-based data platforms; experience with Azure, Databricks, dbt, or comparable technologies is preferred. 
  • Working knowledge of HIPAA requirements and methods for protecting PHI and other sensitive member data, including least-privilege access, masking or de-identification, auditability, and secure handling throughout the data lifecycle. 

Education/Experience 

  • Bachelor's degree in Data Science, Analytics, Computer Science, Information Systems, or a related field, or equivalent practical experience; a master's degree is preferred. 
  • 8+ years of experience in data operations, analytics, business intelligence, data management, or a related environment, including progressively responsible technical, operational, and leadership responsibilities. 
  • 4+ years of direct people-leadership experience, including coaching, performance management, team development, capacity planning, and delivery accountability. 
  • Demonstrated experience managing business-facing data services, reporting operations, data quality, service levels, incidents, priorities, and stakeholder expectations. 
  • Experience overseeing dbt-based analytics or data-modeling work and leading data operations through changes in platforms, architecture, team responsibilities, or operating models. 
  • Strong ability to guide and mentor data analysts, analytics engineers, report developers, or similar data professionals while partnering effectively with data engineers, data scientists, and architects. 
  • Demonstrated success translating organizational objectives into practical data-service priorities, operating processes, and measurable outcomes. 
  • Experience in healthcare and/or retail is a plus; experience operating in a regulated, compliance-driven environment such as HIPAA, SOC 2, or PCI DSS is strongly preferred. 
  • Excellent leadership, written and verbal communication, stakeholder-management, problem-solving, and critical-thinking skills. 
  • Candidates must be able to work from Philadelphia, PA office on Tuesdays and Wednesdays.
  • Must be legally authorized to work in the United States without current or future employer sponsorship. 

Benefits

  • Health Care Plan (Medical, Dental & Vision)
  • Paid Time Off (Vacation, Sick Time Off & Holidays)
  • Company Paid Short Term Disability and Life Insurance
  • Retirement Plan (401k) with Company Match