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Remote Data Engineer Jobs in Johnston, RI (NOW HIRING)

Data Architect

Johnston, RI · Remote

$64.75 - $83.25/hr

... remote global workforce. If you are passionate about leading large-scale cloud and data ... Partner with product owners, domain architects, and data engineering teams to translate business ...

It's why we offer flexible work arrangements that include remote and hybrid opportunities and paid ... The developer works closely with business stakeholders, analytics teams, and data engineering ...

Senior Data Platform Engineer

Providence, RI · On-site +1

$102K - $163K/yr

It's why we offer flexible work arrangements that include remote and hybrid opportunities and paid ... Engineer database platform solutions that align with enterprise security, data governance ...

Configure and manage map services and data publishing workflows to ensure timely and accurate data ... Demonstrated experience with at least one major programming language (e.g., C++, Python, Java, C#)

Configure and manage map services and data publishing workflows to ensure timely and accurate data ... Demonstrated experience with at least one major programming language (e.g., C++, Python, Java, C#)

Showing results 21-40

Remote Data Engineer information

See Johnston, RI salary details

$44.7K

$130.4K

$178.5K

How much do remote data engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote data engineer in Johnston, RI is $130,424.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,100.00 and $138,200.00 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 Johnston, RI?

The most popular types of Data Engineer jobs in Johnston, RI are:

What are popular job titles related to Remote Data Engineer jobs in Johnston, RI?

For Remote Data Engineer jobs in Johnston, RI, the most frequently searched job titles are:

What cities near Johnston, RI are hiring for Remote Data Engineer jobs?

Cities near Johnston, RI with the most Remote Data Engineer job openings:

Infographic showing various Remote Data Engineer job openings in Johnston, RI as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $130,424 per year, or $62.7 per hour.

$64.75 - $83.25/hr

Full-time

Re-posted 16 days ago


Job description

Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.

If you are passionate about leading large-scale cloud and data modernization initiatives that transform enterprise platforms, we would love to hear from you. We are seeking an experienced and dynamic professional to play a key role in assessing, planning, and driving enterprise migration programs across data, applications, and cloud platforms. This role will help clients modernize their technology landscape, optimize legacy systems, and enable scalable, cloud-native architectures aligned with business goals. The Data Architect will support enterprise data initiatives by designing and delivering scalable, modern data architecture solutions with a primary focus on canonical data modeling, semantic data mesh, and realtime streaming architectures using Kafka. This role drives alignment across business domains and enables highquality, governed, and interoperable data for analytics and operational use cases.

Responsibilities:

  1. Develop and enhance canonical data models, semantic models, and domaindriven data contracts to enable crossenterprise data interoperability.
  2. Produce conceptual, logical, and physical data models aligned to business capabilities, modernization goals, and data mesh principles.
  3. Design and implement data architecture patterns to support realtime streaming solutions using Kafka.
  4. Partner with product owners, domain architects, and data engineering teams to translate business needs into scalable, wellgoverned data models.
  5. Ensure consistent application of data governance, metadata management, and lineage standards across data domains.
  6. Architect and optimize data pipelines and storage solutions using AWS (S3, Redshift, Glue, EMR, Lambda) and Snowflake.
  7. Contribute architectural artifacts, modeling standards, and reusable templates for enterprise data modeling.
  8. Support enterprise initiatives around realtime data integration, semantic mesh, and AI/ML enablement through strong data architecture foundations.

Requirements

  • Significant experience with canonical data modeling and enterprisewide conceptual/logical/physical modeling.
  • Strong background in semantic modeling and data mesh design principles.
  • Handson experience with Kafka, including event modeling, schema strategy, and realtime pipeline architecture.
  • Proficiency in AWS data services (S3, Redshift, Glue, EMR, Lambda, EC2) and Snowflake.
  • Strong understanding of ETL/ELT design, data integration patterns, and distributed data systems.
  • Familiarity with data governance, data quality, metadata, and lineage frameworks.
  • Strong SQL skills and proficiency in at least one programming language (Python preferred).
  • Excellent communication skills with the ability to work across technical and business teams.
  • Handson experience with enterprise data catalog and metadata systems.
  • AWS certification (Solutions Architect, Data Analytics Specialty, etc.)

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy,
national origin, ancestry, marital status, protected veteran status, disability
status, or any other basis as protected by federal, state, or local law.