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Data Engineer Jobs in Puerto Rico (NOW HIRING)

Syndeo,-LL

Data Engineer

Carolina, PR · On-site

$65 - $70/hr

We are looking for a Data Engineer to build and operate the pipelines that make this possible, pulling structured and unstructured data out of Artyfica's core services (LAB, RCM, CRM) and the ...

Hondadesanjuan

Data Engineer

San Juan, PR · On-site

$65 - $85/hr

This is not a traditional data engineering role. You'll be joining a newly created Strategy & Innovation team at a pivotal moment in its journey. As one of the early members of the group, you'll won ...

INVID

Data Testing Engineer

San Juan, PR · On-site

$90 - $120/hr

Job Summary We are seeking a detail-oriented and analytical Data Testing Engineer to ensure the accuracy, reliability, and quality of our data platform and reporting solutions. This role plays a ...

Invid, Llc.

Data Testing Engineer

San Juan, PR · On-site

$70 - $100/hr

Job Summary We are seeking a detail-oriented and analytical Data Testing Engineer to ensure the accuracy, reliability, and quality of our data platform and reporting solutions. This role plays a ...

INVID

Data Infrastructure Engineer

San Juan, PR · On-site

$110 - $150/hr

Job Summary We are seeking a talented and driven Data Infrastructure Engineer to support the modernization of the client's data infrastructure and drive enterprise-wide data excellence. In this role ...

Invid, Llc.

Data Infrastructure Engineer

San Juan, PR · On-site

$90 - $130/hr

Job Summary We are seeking a talented and driven Data Infrastructure Engineer to support the modernization of the client's data infrastructure and drive enterprise-wide data excellence. In this role ...

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Data Engineer information

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.
More about Data Engineer jobs

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 Data Engineer jobs in Puerto Rico?

For Data Engineer jobs in Puerto Rico, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Puerto Rico look for?

The top searched job categories for Data Engineer jobs in Puerto Rico are:

What cities in Puerto Rico are hiring for Data Engineer jobs?

Cities in Puerto Rico with the most Data Engineer job openings:

What are popular job titles related to Data Engineer jobs in PR?

For Data Engineer jobs in PR, the most frequently searched job titles are:

Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Puerto Rico as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Data Engineer

Syndeo,-LL

Carolina, PR • On-site

$65 - $70/hr

Other

Posted 5 days ago

Key responsibilities

  • Design, build, and maintain ETL/ELT pipelines that ingest data from core services and the iConnect interoperability engine

  • Build and evolve data warehouse and data lake models that unify clinical and financial data for Data Science consumption

  • Establish and enforce data quality, integrity, lineage, and governance standards across all pipelines

Job description

Salary Range: $65,000.00 To $70,000.00 Annually

Description:

Syndeo's Data Science practice combines clinical and financial data into a single, automated view of the pathology business, a capability that sets our platform apart. We are looking for a Data Engineer to build and operate the pipelines that make this possible, pulling structured and unstructured data out of Artyfica's core services (LAB, RCM, CRM) and the iConnect interoperability engine, and turning it into governed, analytics-ready datasets. This role is foundational to the Data Science layer of Artyfica, working closely with the Data Analyst, Data Scientists, Product Owner, and Scrum Master to keep the ecosystem's intelligence layer fast, trustworthy, and scalable.

Responsibilities of the job include:
  • Design, build, and maintain ETL/ELT pipelines that ingest data from Artyfica's core services (LAB, RCM, CRM) and the iConnect interoperability engine
  • Build and evolve data warehouse and data lake models that unify clinical and financial data for Data Science consumption
  • Establish and enforce data quality, integrity, lineage, and governance standards across all pipelines
  • Partner with Data Analysts and Data Scientists to expose clean, curated, well-documented datasets for reporting and modeling
  • Optimize pipeline performance and scalability as data volume and organizational onboarding grows
  • Implement monitoring and alerting to proactively catch pipeline failures or data quality issues
  • Collaborate with the Software Development team to align data schemas with Artyfica's service-oriented architecture
  • Maintain data catalogs and documentation for all pipelines and datasets
  • Support ingestion of HL7, FHIR, X12, and BAI2 (BTRS) data structures arriving through iConnect
Required skills:
  • Proficient in Python and/or Java for data engineering work
  • Strong SQL skills and hands-on experience with relational databases (Postgres preferred)
  • Experience with ETL/ELT design and orchestration tools (e.g., Airflow or equivalent)
  • Solid understanding of data warehousing and data lake concepts and dimensional modeling
  • Working knowledge of data governance principles and secure handling of protected health information (PHI)
  • Proficient with Git and version control workflows
  • Comfortable operating within Agile Scrum and Kanban practices
  • Logical thinker with strong analytical and problem-solving skills
  • Written and verbal communication skills in both Spanish and English
Desired skills:
  • Experience with healthcare interoperability standards: HL7, FHIR, X12, BAI2
  • Exposure to cloud or analytics platforms such as Snowflake, ClickHouse, or Trino
  • Prior experience integrating financial and clinical data domains
  • Familiarity with streaming or event-driven pipelines (e.g., Kafka)
  • Experience with Docker and containerized data services
Qualifications and training:
  • Bachelor's Degree in Computer Science, Data Engineering, or a related field
  • 3+ years of experience in data engineering
  • Experience with healthcare, RCM, or laboratory data preferred
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