1

Data Processing Jobs in Rhode Island (NOW HIRING)

Data Lakehouse Architect

Middletown, RI · On-site

$63.50 - $81.50/hr

... processing engines such as Spark, Flink, or dbt in lakehouse environments. • Experience implementing data quality, observability, and lineage tooling. • Experience supporting hybrid or multi ...

Confer with data processing or project managers to obtain information on limitations or capabilities for data processing projects. * Consult with customers or other departments on project status ...

Confer with data processing or project managers to obtain information on limitations or capabilities for data processing projects. * Consult with customers or other departments on project status ...

Confer with data processing or project managers to obtain information on limitations or capabilities for data processing projects. * Consult with customers or other departments on project status ...

next page

Showing results 1-20

Data Processing information

See Rhode Island salary details

$12

$19

$34

How much do data processing jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for data processing in Rhode Island is $19.85, according to ZipRecruiter salary data. Most workers in this role earn between $15.77 and $21.88 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Processing position, and why are they important?

To thrive in Data Processing, you need strong analytical abilities, attention to detail, and proficiency with spreadsheets and database management, often supported by an associate's degree or relevant experience. Familiarity with tools like Microsoft Excel, SQL, or data entry software, as well as certifications such as Certified Data Processor (CDP), are frequently expected. Strong organizational skills, time management, and the ability to troubleshoot problems efficiently are valued soft skills. These competencies are crucial for ensuring data accuracy, meeting deadlines, and supporting smooth information operations within an organization.

What is a data processing job role?

A data processing job involves collecting, organizing, and converting raw data into a usable format for analysis or reporting. It often requires skills in data management tools, attention to detail, and knowledge of data formats and software such as Excel, SQL, or specialized processing programs.

What are the typical daily responsibilities of someone working in Data Processing?

A typical day for a Data Processing professional involves entering, validating, and updating records in databases or spreadsheets to ensure data integrity. You may also be responsible for generating reports, cleaning large data sets, and identifying discrepancies or errors for correction. Collaboration with team members or departments is common to clarify data requirements and resolve issues. Staying organized and attentive to detail is essential because the quality of processed data can impact decision-making across the organization.

What is a Data Processing job?

A Data Processing job involves collecting, organizing, and managing data to ensure accuracy and accessibility. Professionals in this role use software tools to input, clean, analyze, and process data for businesses or organizations. They may also generate reports and automate workflows to streamline data handling. Strong attention to detail and proficiency in data management tools are essential for success in this field.

Is AI replacing data entry jobs?

AI is automating many data entry tasks by using machine learning and optical character recognition, which can increase efficiency and reduce manual labor. However, data processing jobs still require human oversight for complex or unstructured data, and roles involving data validation, analysis, and management remain essential. Professionals in data processing should develop skills in AI tools and data management to stay relevant.

What is the highest paying job in data?

In data-related fields, roles such as Data Science Director, Chief Data Officer, or Senior Data Architect tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in data analysis, machine learning, and leadership, along with extensive experience and relevant certifications.
What are the most commonly searched types of Data Processing jobs in Rhode Island? The most popular types of Data Processing jobs in Rhode Island are:
What are popular job titles related to Data Processing jobs in Rhode Island? For Data Processing jobs in Rhode Island, the most frequently searched job titles are:
What job categories do people searching Data Processing jobs in Rhode Island look for? The top searched job categories for Data Processing jobs in Rhode Island are:
Infographic showing various Data Processing job openings in Rhode Island as of July 2026, with employment types broken down into 72% Full Time, 4% Part Time, 8% Temporary, and 16% Contract. Highlights an 76% In-person, and 24% Remote job distribution, with an average salary of $41,281 per year, or $19.8 per hour.
Data Lakehouse Architect

Data Lakehouse Architect

SEACORP

Middletown, RI • On-site

$63.50 - $81.50/hr

Full-time

Re-posted 18 days ago


Job description

Job Summary:
SEACORP is seeking a well-qualified Data Lakehouse Architect to lead the design, implementation, and evolution of a modern, tiered data platform. This role will define the target-state architecture for a lakehouse environment and partner with various teams to establish architectural standards and enable high-quality data products.
Responsibilities:
• Design and document lakehouse architecture using Kafka for streaming ingestion, Iceberg for table format and data management, S3 and/or CEPH for object storage, and Trino for distributed SQL query access.
• Define architecture for data partitioning, compaction, schema evolution, metadata management, table maintenance, and lifecycle policies.
• Architect data ingestion frameworks for both real-time and batch workloads, including event-driven and CDC-based integration patterns.
• Establish scalable, resilient, and secure storage patterns across cloud and on-premises or hybrid object storage environments.
• Define governance patterns including access control, encryption, data retention, lineage, auditability, and compliance integration.
• Partner with data engineers to optimize query performance, file sizing, partitioning strategy, and workload concurrency in Trino and related engines.
• Lead engineering teams and review designs, code, and deployment approaches for alignment with target architecture.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 7+ years of experience in data engineering, data architecture, or platform architecture roles.
• 3+ years of experience designing and implementing modern data lake or lakehouse architectures in production environments.
• Hands-on experience with Apache Kafka for streaming data ingestion, event architecture, or real-time data integration.
• Hands-on experience with Apache Iceberg or a similar open table format in large-scale analytical environments.
• Experience designing data platforms on object storage, including Amazon S3, CEPH, or equivalent S3-compatible storage systems.
• Experience with Trino or similar distributed SQL query engines for interactive analytics over large datasets.
• Strong understanding of distributed systems principles, including scalability, fault tolerance, consistency tradeoffs, and performance tuning.
• Experience with data modeling, schema design, partitioning strategy, and optimization for analytical workloads.
• Experience with security architecture including role-based access control, encryption, and data governance controls.
• Experience creating architecture documentation, technical standards, and implementation roadmaps.
• Strong knowledge of batch and streaming pipeline patterns, including CDC, event-driven design, and ingestion orchestration.
• Required knowledge of Atlassian Tool Suite, Git, and Linux.
• Ability to work in a fast-paced work environment.
• Able to collaborate with others while being able to handle independent tasking.
• Ability to learn new technologies quickly.
Preferred:
• Master’s degree in Computer Science, Data Engineering, Distributed Systems, or a related field.
• Desired knowledge in the areas of Databases, SQL and No-SQL (Postgres, MongoDB), Apache Data Frameworks (Kafka, Spark, Iceberg, OpenMetadata, Ranger), Data Infrastructure (Ceph, S3, MinIO/Parquet, REST, Nessie, Druid), Data APIs (Trino, Metabase, MLLib, Superset).
• Experience with Team Submarine, SWFTS, US Navy program offices, TI/APB cycle.
• Experience with metadata catalogs such as Hive Metastore, AWS Glue Catalog, Nessie, or Polaris.
• Familiarity with data processing engines such as Spark, Flink, or dbt in lakehouse environments.
• Experience implementing data quality, observability, and lineage tooling.
• Experience supporting hybrid or multi-cloud data architectures.
• Familiarity with Kubernetes-based deployment and platform operations.
• Experience with regulated data environments and compliance frameworks such as SOC 2, HIPAA, PCI-DSS, or FedRAMP.
• Exceptional Qualifications: Candidates possessing knowledge in these technologies will be considered exceptional candidates including Kubernetes, RKE2, containerization, Helm, AI/ML APIs, SparkML, AI/ML Integration (LLM Development Stack), DPCN training, PINN training, or agentic development integration.
• Recognized expertise designing enterprise-scale lakehouse platforms using open standards and interoperable tooling.
• Experience delivering software and systems for Team Submarine or SWFTS programs, including experience with the Submarine platform tactical systems.
• Deep production experience with Kafka + Iceberg + Trino architectures, including performance optimization and operational scaling.
• Experience building platforms that span cloud and on-premises object storage, especially S3 and CEPH in hybrid deployments.
• Demonstrated success leading architecture for high-volume, low-latency, and mission-critical data ecosystems.
• Ability to make principled architectural decisions regarding catalogs, table maintenance, file formats, compaction, and query federation.
• Strong record of mentoring senior engineers and establishing architecture review processes and engineering standards.
• Experience leading major data platform migrations from legacy warehouse, Hadoop, or tightly coupled ETL ecosystems to modern lakehouse architectures.
• Ability to balance long-term architectural integrity with pragmatic delivery timelines and business value.
Company:
SEACORP corporation is a veteran-owned business focusing on systems engineering. Founded in 1981, the company is headquartered in Middletown, USA, with a team of 501-1000 employees. The company is currently Late Stage.

SEACORP logo

About SEACORP

Sourced by ZipRecruiter

Industry

Guided missile and space vehicle manufacturing

Company size

501 - 1,000 Employees

Headquarters location

Middletown, RI, US

Year founded

1981