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Remote Data Engineer- Mid Level
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Scorecard
Based on Rhode Island data
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What they do
A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.
$118,915 / year median in Rhode Island
+11% projected growth
Job Description
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Salary Not Available
Position range in Rhode Island $91k
- $148k Per Year Remote Data Engineer
- Mid Level
Insight Global
Occupation:
Software Developers
Location:
Woonsocket, RI
- 02895
Job Type:
Full Time (30 Hours or More)
Posted:
08/22/2026
Positions available: 1
Source:
NLX
Web Site:
usnlx.com
Job #: 296080516
Job Requirements and Properties
Help for Job Requirements and Properties. Opens a new window. Work Onsite
Full Time Schedule
Full Time
Job Description
Help for Job Description. Opens a new window. Job Description
We are seeking a highly skilled Data Engineer to design, build, and support scalable data solutions that power critical business reporting, analytics, and operational workloads. This individual will be responsible for developing robust data pipelines, optimizing data platforms, ensuring data quality, and collaborating across engineering and business teams to deliver reliable, high-quality data products.
Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data across the organization.
Build and optimize complex SQL queries, stored procedures, and data workflows for performance and reliability.
Develop Python-based solutions for data processing, automation, and pipeline orchestration.
Design and maintain data models, including dimensional models, normalized schemas, and analytical data structures.
Support and enhance enterprise data warehouse environments, including Snowflake, Teradata, PostgreSQL, Redshift, or BigQuery.
Implement data quality monitoring, validation frameworks, and operational controls to ensure data accuracy and integrity.
Monitor and troubleshoot production data pipelines, ensuring fault tolerance, observability, and operational excellence.
Partner closely with Data Engineering, Infrastructure, Product, Analytics, and Business teams to understand requirements and deliver scalable solutions.
Support cloud-based data infrastructure and data movement across platforms and services.
Contribute to data governance, security, compliance, and best practices across the data ecosystem.
Participate in production support, root cause analysis, and continuous improvement initiatives.
Drive performance tuning and optimization of large-scale datasets and data processing workloads.
This person is expected to be paid $50
- 55hr
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day.
We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.
To learn more about how we collect, keep, and process your private information, please review
Insight Global's Workforce Privacy Policy:
https://insightglobal.com/workforce-privacy-policy/.
Skills and Requirements
- Strong proficiency or 5-7 years in SQL, including advanced querying, joins, optimization, and performance tuning.
- Strong proficiency in Python for data processing, automation, and pipeline development.
- Deep understanding of data modeling, including dimensional modeling, normalization, and schema design.
- Hands-on experience designing and managing ETL/ELT pipelines using Airflow, dbt, or similar orchestration tools.
- Experience with enterprise data warehousing platforms such as Snowflake, Teradata, Redshift, BigQuery, or PostgreSQL.
- Experience working with cloud platforms such as Azure or Google Cloud Platform (GCP).
- Familiarity with cloud storage and compute services.
- Experience with batch and streaming data processing technologies such as Kafka.
- Working knowledge of containerization and deployment technologies, including Docker and Kubernetes.
- Experience supporting cloud-first data platforms and large-scale data environments.
- Strong debugging, troubleshooting, and problem-solving skills.
- Excellent communication skills with the ability to translate technical concepts for non-technical stakeholders.
- Experience owning and supporting production-grade data pipelines in a high-availability environment.
- Experience implementing data quality, monitoring, and observability frameworks.
- Understanding of data governance, security, privacy, and compliance requirements.
- Experience collaborating across multiple engineering teams and business stakeholders.
- Demonstrated ownership mindset with a focus on reliability, operational excellence, and continuous improvement.