2

Remote Data Engineer Jobs in Granby, CT (NOW HIRING)

GenAI Data Engineer

Hartford, CT · Remote

$117K - $140K/yr

As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure. You will collaborate closely with data ...

GenAI Data Engineer

Hartford, CT · On-site +1

$115K - $138K/yr

As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure. You will collaborate closely with data ...

Sr Staff Data Engineer - GE07DE We're determined to make a difference and are proud to be an ... This role can have a Hybrid or Remote work schedule. Candidates who live near one of our locations ...

Data & AI Delivery Lead

Hartford, CT · On-site +1

$156K - $234K/yr

Dir Data Engineering - GE06AE We're determined to make a difference and are proud to be an ... Hybrid / Or Remote This role can have a Hybrid or Remote work schedule. Candidates who live near ...

This role can have a Hybrid or Remote work arrangement. Candidates who live near one of our office ... Experience with data engineering, ETL technology, and conversation UX is a plus. * Experience with ...

next page

Showing results 1-20

Remote Data Engineer information

See Granby, CT salary details

$45.6K

$132.9K

$181.9K

How much do remote data engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote data engineer in Granby, CT is $132,942.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,300.00 and $140,900.00 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 Granby, CT?

The most popular types of Data Engineer jobs in Granby, CT are:

What are popular job titles related to Remote Data Engineer jobs in Granby, CT?

For Remote Data Engineer jobs in Granby, CT, the most frequently searched job titles are:

What cities near Granby, CT are hiring for Remote Data Engineer jobs?

Cities near Granby, CT with the most Remote Data Engineer job openings:

Infographic showing various Remote Data Engineer job openings in Granby, CT as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $132,942 per year, or $63.9 per hour.

GenAI Data Engineer

Tiger Analytics Inc.

Hartford, CT • Remote

$117K - $140K/yr

Full-time

Re-posted 23 days ago


Job description

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.

We are seeking an experienced Data Engineer with expertise in Dataiku to join our data team. As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure. You will collaborate closely with data scientists, analysts, and other stakeholders to ensure efficient data flow and support data-driven decision making across the organization.

Requirements

  • Design and implement robust data pipelines that ingest, process, and store unstructured data formats at scale within Snowflake and GCP.
  • Leverage Snowflake’s unstructured data capabilities (Directory Tables, Scoped URLs, Snowpark) to make "dark data" queryable and actionable.
  • Build and maintain cloud-native ETL/ELT processes using BigQuery, Cloud Storage, and Dataflow, ensuring seamless integration between GCP and Snowflake.
  • Instead of just using LLMs, you will integrate AI tools (OCR, NLP entities, Document AI) into the engineering flow to transform unstructured blobs into structured insights.
  • Tune complex SQL queries and Python-based processing jobs to handle petabyte-scale environments efficiently.

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.