CPT Data Platform Engineer Jobs
Data Platform Engineer roles involve designing and maintaining large-scale data infrastructure, which maps directly to graduate programs in computer science, data engineering, and information systems. CPT authorization requires your DSO to confirm the work is an integral part of your curriculum, so securing a role with clear technical responsibilities strengthens that case.
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Get Access To All JobsINTRODUCTION
At Plymouth Rock, a fast-growing, analytics-driven insurer, we believe data science can redefine how insurance operates. As a Data Engineer Intern/Co-op with our Enterprise Advanced Analytics team, you will work with a team of top-tier data scientists to generate breakthrough insights that drive profitable growth, operational excellence, and competitive advantage. You will work with the team to help architect and manage the data pipelines that connect internal systems, third-party sources, and advanced analytical platforms, directly enabling our most strategic research initiatives.
Responsibilities
- Assist in modernizing legacy data pipelines into Python-based, cloud-native workflows using AWS Step Functions, AWS Glue, and S3.
- Build and improve ingestion pipelines that move data from SQL Server and other on-prem + cloud sources into AWS (e.g., S3-backed data lake).
- Improve pipeline performance, efficiency, and scalability (e.g., partitioning strategies, incremental loads, reduced runtime/cost).
- Implement data quality checks and operational safeguards to support reliable, repeatable (idempotent) runs (e.g., validation rules, anomaly checks, retry-safe processing).
- Contribute to reusable Python modules for ingestion, transformations, quality checks, logging, and alerting.
- Partner with data scientists/ML engineers to prepare curated datasets for SageMaker training/inference workflows.
- Document code, workflows, and runbooks; keep documentation current as pipelines evolve.
BASIC QUALIFICATIONS
- Currently pursuing or have completed a Master's in Computer Science, Information Systems, Data Engineering (or related).
- Experience (projects, internships, or coursework) building Python + SQL data pipelines or data-intensive workflows.
- Familiarity with AWS services commonly used in data platforms, including S3, Glue, Step Functions (hands-on experience preferred).
- Experience working with SQL Server (or similar relational databases) and writing performant SQL.
- Comfort with Linux and bash; able to debug jobs and inspect logs.
- Familiarity with CI/CD, Git, and basic testing practices.
- Exposure to hybrid connectivity patterns (e.g., VPN/Direct Connect, hosted agents, secure credential management) or tools for extracting from on-prem sources.
- Familiarity with data lake formats and practices (Parquet, partitioning, schema evolution).
- Exposure to monitoring/alerting (CloudWatch, Datadog) and data quality frameworks/patterns.
- Interest in ML data prep / feature pipelines for SageMaker.
COMPENSATION
- Salary Range: $25/hr - $30/hr. Actual compensation will vary based on multiple factors, including employee knowledge and experience, role scope, business needs, geographical location, and internal equity.
ABOUT THE COMPANY
The Plymouth Rock Company and its affiliated group of companies write and manage over $2 billion in personal and commercial auto and homeowner's insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”
INTRODUCTION
At Plymouth Rock, a fast-growing, analytics-driven insurer, we believe data science can redefine how insurance operates. As a Data Engineer Intern/Co-op with our Enterprise Advanced Analytics team, you will work with a team of top-tier data scientists to generate breakthrough insights that drive profitable growth, operational excellence, and competitive advantage. You will work with the team to help architect and manage the data pipelines that connect internal systems, third-party sources, and advanced analytical platforms, directly enabling our most strategic research initiatives.
Responsibilities
- Assist in modernizing legacy data pipelines into Python-based, cloud-native workflows using AWS Step Functions, AWS Glue, and S3.
- Build and improve ingestion pipelines that move data from SQL Server and other on-prem + cloud sources into AWS (e.g., S3-backed data lake).
- Improve pipeline performance, efficiency, and scalability (e.g., partitioning strategies, incremental loads, reduced runtime/cost).
- Implement data quality checks and operational safeguards to support reliable, repeatable (idempotent) runs (e.g., validation rules, anomaly checks, retry-safe processing).
- Contribute to reusable Python modules for ingestion, transformations, quality checks, logging, and alerting.
- Partner with data scientists/ML engineers to prepare curated datasets for SageMaker training/inference workflows.
- Document code, workflows, and runbooks; keep documentation current as pipelines evolve.
BASIC QUALIFICATIONS
- Currently pursuing or have completed a Master's in Computer Science, Information Systems, Data Engineering (or related).
- Experience (projects, internships, or coursework) building Python + SQL data pipelines or data-intensive workflows.
- Familiarity with AWS services commonly used in data platforms, including S3, Glue, Step Functions (hands-on experience preferred).
- Experience working with SQL Server (or similar relational databases) and writing performant SQL.
- Comfort with Linux and bash; able to debug jobs and inspect logs.
- Familiarity with CI/CD, Git, and basic testing practices.
- Exposure to hybrid connectivity patterns (e.g., VPN/Direct Connect, hosted agents, secure credential management) or tools for extracting from on-prem sources.
- Familiarity with data lake formats and practices (Parquet, partitioning, schema evolution).
- Exposure to monitoring/alerting (CloudWatch, Datadog) and data quality frameworks/patterns.
- Interest in ML data prep / feature pipelines for SageMaker.
COMPENSATION
- Salary Range: $25/hr - $30/hr. Actual compensation will vary based on multiple factors, including employee knowledge and experience, role scope, business needs, geographical location, and internal equity.
ABOUT THE COMPANY
The Plymouth Rock Company and its affiliated group of companies write and manage over $2 billion in personal and commercial auto and homeowner's insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”
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Get Access To All JobsData Platform Engineer CPT: Frequently Asked Questions
Does a Data Platform Engineer internship qualify for CPT?
Yes, if the role is an integral part of your program of study and your DSO authorizes it. Data platform engineering work, covering tasks like building data pipelines, managing cloud storage systems, and orchestrating workflows, aligns clearly with graduate programs in computer science, data engineering, or information systems. Your offer letter must detail specific technical duties so your DSO can confirm the curriculum connection.
Can I work full-time as a Data Platform Engineer on CPT?
Full-time CPT, defined as 20 or more hours per week by USCIS, is permitted but affects your OPT eligibility. Twelve or more months of full-time CPT eliminates your OPT entirely, including STEM OPT. Part-time CPT, under 20 hours per week, does not count against OPT regardless of duration. Confirm the hours on your offer letter with your DSO before accepting a full-time role.
What technical skills make a CPT application stronger for this role?
DSOs look for a direct connection between your coursework and job duties. For data platform engineering, documented experience with distributed systems, cloud platforms such as AWS or Google Cloud, SQL and NoSQL databases, and workflow orchestration tools like Apache Airflow strengthens the curriculum link. Reference specific course titles and projects in your CPT request that match the technical scope of the role.
How do I find Data Platform Engineer employers familiar with CPT?
Search Migrate Mate to browse data platform engineering roles at employers with documented work authorization experience. Companies already enrolled in E-Verify and with prior F-1 hiring history tend to process CPT paperwork faster, since their HR teams understand the I-20 authorization step. Targeting those employers reduces the risk of offer rescissions caused by unfamiliarity with CPT timelines.
How does CPT as a Data Platform Engineer affect my future H-1B eligibility?
CPT itself does not affect H-1B visa eligibility, but the downstream OPT impact matters. If you exhaust full-time CPT beyond 12 months, you lose OPT, which is the primary bridge to H-1B sponsorship for most F-1 graduates. Keeping CPT part-time or completing it within one semester preserves your OPT and STEM OPT options, giving you up to three years of work authorization to pursue H-1B sponsorship through an employer.