2

Remote Data Engineer Jobs in Puerto Rico (NOW HIRING)

Work Type: Full-time, permanent Location: 100% Remote Reporting Line: International teams in the US ... This role plays a critical technical function by connecting healthcare data with media and ...

... Remote Serve as a Senior Engineer - Execution Systems in a hybrid work environment, designing ... engineers and share best practices in historian configuration and data governance. • Drive ...

... data centers and critical manufacturing facilities). You will work with Strategic Account Sales ... This is a remote position. Candidates can be located anywhere in the US. This role is contributing ...

Technical Program Manager

San Juan, PR · Remote

$126K - $163K/yr

... engineering teams and modernizing technology & data platforms. Our delivery models are tailored to ... Role is remote Preferred: * Experience using Microsoft Word, Excel, and PowerPoint * Experience ...

This is a primarily remote role supporting enterprise Epic implementation, with minimal travel and ... engineering teams and modernizing technology & data platforms. Our delivery models are tailored to ...

Hospital Billing Operator

San Juan, PR · Remote

$18 - $23/hr

This is a primarily remote role supporting an enterprise Epic implementation, with minimal travel ... engineering teams and modernizing technology & data platforms. Our delivery models are tailored to ...

The role requires hands-on engineering depth across OT/IIoT platforms, combined with the ability to ... Familiarity with SIMCA-Online or similar multivariate data analysis (MVDA) platforms

Linguist III

PR · Remote

Infrastructure Engineering - Linguist III Location: US - NY - Remote Duration:8 months Job Title ... for data analysis are a plus. Must be able to independently work through complex requests and ...

Remote/hybrid experience preferred * A minimum of 2-4 years' administrative experience and/or ... Using real world data, our engineers normalize data to create analytic dashboards with drill down ...

Remote/hybrid experience preferred * A minimum of 2-4 years' administrative experience and/or ... Using real world data, our engineers normalize data to create analytic dashboards with drill down ...

next page

Showing results 1-20

Remote Data Engineer information

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.

Can a data engineer work remotely?

Yes, data engineers can work remotely, especially as many companies adopt flexible work arrangements. Remote data engineering roles often require strong skills in cloud platforms, data pipelines, and collaboration tools, and may involve regular virtual communication with teams. The feasibility depends on the company's policies and the specific job requirements.

Will AI replace data engineer?

AI is unlikely to fully replace data engineers, as their role involves designing, building, and maintaining data pipelines and infrastructure that require human oversight and expertise. Instead, AI tools can augment their work by automating routine tasks, allowing data engineers to focus on complex problem-solving and system architecture. Skills in programming, cloud platforms, and data management remain essential for the role.

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.

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 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 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.

What engineers make $500,000?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires specialized certifications, leadership roles, and a strong track record of managing complex data infrastructure.

How to make $1000 a week remote?

A remote data engineer can earn $1000 or more per week by working full-time for a company, freelancing on project-based platforms, or offering specialized skills such as data pipeline development, cloud computing, or machine learning. Building a strong portfolio, gaining relevant certifications, and mastering tools like SQL, Python, and cloud services can increase earning potential.
What are the most commonly searched types of Data Engineer jobs in Puerto Rico? The most popular types of Data Engineer jobs in Puerto Rico are:
What are popular job titles related to Remote Data Engineer jobs in Puerto Rico? For Remote Data Engineer jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineer jobs in Puerto Rico look for? The top searched job categories for Remote Data Engineer jobs in Puerto Rico are:

Data Analyst Pharmaceutical Industry

Julius 2 Grow

Remote

Full-time

Posted 14 days ago


Job description

Work Type: Full-time, permanent
Location: 100% Remote
Reporting Line: International teams in the US and Europe
Language Requirement: Advanced English (must-have)
Time Zone Preference: US East Coast

Role Overview

We are seeking a highly analytical and detail-oriented Data Analyst to support pharmaceutical brand, commercial (marketing), and analytics teams. This role plays a critical technical function by connecting healthcare data with media and marketing insights to drive clear, actionable business outcomes.

The ideal candidate is comfortable working with complex and imperfect data, applies strong statistical reasoning, and can translate sophisticated analyses into compelling insights for both technical and non-technical stakeholders. This is a fully remote role, collaborating closely with cross-functional teams across the US and Europe.

Key Responsibilities
  • Perform advanced SQL-based data transformations, integrating multiple internal and external data sources (e.g., claims, media, CRM, EHR-derived datasets).

  • Define, validate, and govern metrics aligned with pharmaceutical business needs (e.g., brand performance, HCP engagement, patient journeys).

  • Apply statistical analysis to identify trends, key drivers, and ensure analytical rigor in recommendations.

  • Maintain and evolve analytical datasets and workflows as new data is ingested.

  • Conduct in-depth exploratory data analysis (EDA) to uncover patterns, anomalies, and opportunities within complex healthcare datasets.

  • Translate analytical findings into clear, actionable insights tailored to stakeholders across marketing, analytics, strategy, and leadership teams.

  • Manually clean, normalize, and structure data to ensure quality and analytical readiness for deep-dive analyses.

  • Prepare datasets to support advanced analytics, including exploratory and explanatory AI/ML applications.

  • Develop dashboards and data visualizations that clearly communicate insights and support decision-making.

  • Collaborate cross-functionally with data science, technology, media, strategy, and client-facing teams.

  • Document methodologies, assumptions, and data limitations to ensure transparency and reproducibility.

Required Qualifications
  • Bachelors degree in Analytics, Statistics, Mathematics, Data Science, Economics, or a related field.

  • 24 years of experience defining and validating metrics within the pharmaceutical, healthcare, or life sciences industry.

  • Strong SQL proficiency, including complex joins, transformations, and performance optimization.

  • Experience working with cloud data warehouses (e.g., BigQuery).

  • Solid foundation in statistics and analytical reasoning (trend analysis, hypothesis testing, segmentation).

  • Proven experience with exploratory data analysis and large, complex datasets.

  • Ability to simplify complex data and insights for diverse audiences.

  • Experience with data visualization tools (Tableau, Power BI, Looker, or similar).

  • Strong collaboration skills and experience working with cross-functional teams.

  • Advanced English communication skills (required).

Preferred Qualifications
  • Experience with pharmaceutical commercial or media data (claims, prescriptions, CRM, hub, or media datasets).

  • Familiarity with AI/ML concepts and data preparation for modeling.

  • Experience using Python or R for analytics and data manipulation.

  • Understanding of pharma compliance, privacy, and data governance.

  • Previous experience working remotely with distributed, international teams across multiple time zones.

Key Competencies
  • Strong analytical rigor and attention to detail

  • Business-oriented problem-solving mindset

  • Clear, concise communication skills

  • Comfort working with ambiguity and imperfect data

  • Curiosity and continuous learning mentality

  • Team-oriented and collaborative approach