Data Manager Visa Sponsorship Jobs in New Jersey
Data manager roles in New Jersey draw strong interest from international candidates, with major employers concentrated in Jersey City, Newark, and Princeton spanning finance, pharmaceuticals, and technology. Firms like Johnson & Johnson, Cognizant, and major financial institutions along the Hudson waterfront regularly hire data managers and have established visa sponsorship programs.
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The Princeton DMIA Integration team is looking for a Data Engineer to own and evolve our data integration practice. You will be responsible for ingesting data from enterprise source systems into our data warehouse platform — what the CIO office refers to as system-to-data-repository integrations. You will play a key role in our migration to a cloud-native data platform, with candidates expected to bring expertise in modern tooling such as Microsoft Fabric, Snowflake with dbt and Fivetran, or Databricks. The existing data warehouse technologies include IBM DataStage, SQL, Oracle, and Shell-based pipelines running on on-premises Linux infrastructure.
Responsibilities:
Architect, Design, Develop:
- Design, build, and maintain ETL/ELT pipelines to ingest, transform, and load data from source systems into the enterprise data warehouse.
- Lead the migration of on-premises data pipelines to the organization’s future cloud-native data platform (one of Fabric, Snowflake + dbt + Fivetran, or Databricks).
- Implement and enforce data quality checks, data lineage tracking, and pipeline observability across all integration workflows.
- Ensure data security and compliance requirements are met, including encryption at rest and in transit, and access controls aligned with IAM policies.
- Optimize pipeline performance, scheduling, and resource utilization across batch and incremental load patterns.
Collaborate and Coordinate:
- Partner with data analysts, BI developers, and source system owners to understand data requirements and translate them into robust ingestion pipelines.
Production Support:
- Operate and support ingestion and transformation pipelines.
- Develop and maintain data pipeline documentation, data dictionaries, and SLA agreements for ingestion jobs.
- Participate in on-call production support rotation and respond to integration incidents per SLA.
- Contribute to CI/CD pipeline setup and DevOps practices for data integration deployments.
QUALIFICATIONS
Essential Qualifications:
- CORE SKILLS
+ Linux / Shell scripting
+ Python programming
+ SQL (query authoring and data validation)
+ Basic networking (DNS, HTTP/S, TCP/IP, proxies, firewalls)
+ Cloud infrastructure fundamentals (any major provider)
+ IAM: LDAP, Active Directory, OAuth 2.0, certificate management
- 5+ years of proven experience with enterprise ETL/ELT tooling
- Advanced SQL skills across multiple platforms (Oracle, SQL Server, PostgreSQL)
- Strong Python programming skills for data transformation, scripting, and pipeline automation
- Shell scripting proficiency for batch job automation on Linux/Unix servers
- Hands-on experience with at least one cloud data platform: Microsoft Fabric, Snowflake (with dbt and/or Fivetran), or Databricks
- Experience with dbt (data build tool) for transformation layer development
- Linux/Unix systems fluency including file management, cron scheduling, and process monitoring
- Understanding of data warehousing concepts: dimensional modelling, star/snowflake schemas, slowly changing dimensions
- Familiarity with basic networking, storage, and cloud infrastructure concepts
- Experience with IAM and access control: LDAP, Active Directory, and database-level permission management
- Working knowledge of REST APIs for source system data extraction and pipeline orchestration
- Ability to document data flows, pipeline architecture, and transformation logic clearly
- Education: Bachelor’s degree in computer science
PREFERRED QUALIFICATIONS:
- 7+ years proven experience with enterprise ETL/ELT tooling
- Familiarity with orchestration tools such as Apache Airflow, Azure Data Factory, or Prefect
- Exposure to streaming or near-real-time ingestion patterns (Kafka, Kinesis, Event Hubs)
- Experience with data quality frameworks (Great Expectations, Soda, or equivalent)
- Cloud platform certifications (Azure, AWS, or GCP data engineering tracks)
Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.
The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.
If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.
The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
STANDARD WEEKLY HOURS: 36.25
ELIGIBLE FOR OVERTIME: No
BENEFITS ELIGIBLE: Yes
PROBATIONARY PERIOD: 180 days
ESSENTIAL SERVICES PERSONNEL (see policy for detail): No
PHYSICAL CAPACITY EXAM REQUIRED: No
VALID DRIVER’S LICENSE REQUIRED: No
EXPERIENCE LEVEL: Mid-Senior Level
SALARY RANGE: $120,000 to $135,000
Overview:
The Princeton DMIA Integration team is looking for a Data Engineer to own and evolve our data integration practice. You will be responsible for ingesting data from enterprise source systems into our data warehouse platform — what the CIO office refers to as system-to-data-repository integrations. You will play a key role in our migration to a cloud-native data platform, with candidates expected to bring expertise in modern tooling such as Microsoft Fabric, Snowflake with dbt and Fivetran, or Databricks. The existing data warehouse technologies include IBM DataStage, SQL, Oracle, and Shell-based pipelines running on on-premises Linux infrastructure.
Responsibilities:
Architect, Design, Develop:
- Design, build, and maintain ETL/ELT pipelines to ingest, transform, and load data from source systems into the enterprise data warehouse.
- Lead the migration of on-premises data pipelines to the organization’s future cloud-native data platform (one of Fabric, Snowflake + dbt + Fivetran, or Databricks).
- Implement and enforce data quality checks, data lineage tracking, and pipeline observability across all integration workflows.
- Ensure data security and compliance requirements are met, including encryption at rest and in transit, and access controls aligned with IAM policies.
- Optimize pipeline performance, scheduling, and resource utilization across batch and incremental load patterns.
Collaborate and Coordinate:
- Partner with data analysts, BI developers, and source system owners to understand data requirements and translate them into robust ingestion pipelines.
Production Support:
- Operate and support ingestion and transformation pipelines.
- Develop and maintain data pipeline documentation, data dictionaries, and SLA agreements for ingestion jobs.
- Participate in on-call production support rotation and respond to integration incidents per SLA.
- Contribute to CI/CD pipeline setup and DevOps practices for data integration deployments.
QUALIFICATIONS
Essential Qualifications:
- CORE SKILLS
+ Linux / Shell scripting
+ Python programming
+ SQL (query authoring and data validation)
+ Basic networking (DNS, HTTP/S, TCP/IP, proxies, firewalls)
+ Cloud infrastructure fundamentals (any major provider)
+ IAM: LDAP, Active Directory, OAuth 2.0, certificate management
- 5+ years of proven experience with enterprise ETL/ELT tooling
- Advanced SQL skills across multiple platforms (Oracle, SQL Server, PostgreSQL)
- Strong Python programming skills for data transformation, scripting, and pipeline automation
- Shell scripting proficiency for batch job automation on Linux/Unix servers
- Hands-on experience with at least one cloud data platform: Microsoft Fabric, Snowflake (with dbt and/or Fivetran), or Databricks
- Experience with dbt (data build tool) for transformation layer development
- Linux/Unix systems fluency including file management, cron scheduling, and process monitoring
- Understanding of data warehousing concepts: dimensional modelling, star/snowflake schemas, slowly changing dimensions
- Familiarity with basic networking, storage, and cloud infrastructure concepts
- Experience with IAM and access control: LDAP, Active Directory, and database-level permission management
- Working knowledge of REST APIs for source system data extraction and pipeline orchestration
- Ability to document data flows, pipeline architecture, and transformation logic clearly
- Education: Bachelor’s degree in computer science
PREFERRED QUALIFICATIONS:
- 7+ years proven experience with enterprise ETL/ELT tooling
- Familiarity with orchestration tools such as Apache Airflow, Azure Data Factory, or Prefect
- Exposure to streaming or near-real-time ingestion patterns (Kafka, Kinesis, Event Hubs)
- Experience with data quality frameworks (Great Expectations, Soda, or equivalent)
- Cloud platform certifications (Azure, AWS, or GCP data engineering tracks)
Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.
The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.
If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.
The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
STANDARD WEEKLY HOURS: 36.25
ELIGIBLE FOR OVERTIME: No
BENEFITS ELIGIBLE: Yes
PROBATIONARY PERIOD: 180 days
ESSENTIAL SERVICES PERSONNEL (see policy for detail): No
PHYSICAL CAPACITY EXAM REQUIRED: No
VALID DRIVER’S LICENSE REQUIRED: No
EXPERIENCE LEVEL: Mid-Senior Level
SALARY RANGE: $120,000 to $135,000
Data Manager Job Roles in New Jersey
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Search Data Manager Jobs in New JerseyData Manager Jobs in New Jersey: Frequently Asked Questions
Which companies sponsor visas for data managers in New Jersey?
Pharmaceutical companies including Johnson & Johnson, Merck, and Novartis have active sponsorship histories for data manager roles at their New Jersey campuses. Financial services firms in Jersey City, such as JPMorgan Chase and Goldman Sachs, also sponsor regularly. IT services companies like Cognizant and Infosys, which maintain large New Jersey operations, are among the most consistent H-1B visa filers for data management positions.
Which visa types are most common for data manager roles in New Jersey?
The H-1B is the most common visa for data manager positions in New Jersey, as the role typically qualifies as a specialty occupation requiring a bachelor's degree or higher in a relevant field such as computer science, information systems, or statistics. Some candidates with advanced degrees pursue the EB-2 or EB-3 immigrant visa pathways. Intracompany transferees from multinational firms may also enter on L-1B visas.
Which cities in New Jersey have the most data manager sponsorship jobs?
Jersey City leads due to its proximity to Manhattan and concentration of financial services and technology employers. Newark follows, supported by its role as a regional corporate hub and home to Prudential Financial. Princeton and the Route 1 corridor have significant activity from pharmaceutical and biotech firms. Parsippany and Bridgewater also see steady demand, anchored by life sciences and consumer goods companies with large campuses.
How to find data manager visa sponsorship jobs in New Jersey?
Migrate Mate filters job listings specifically by visa sponsorship availability, making it straightforward to browse data manager openings in New Jersey without sorting through positions that don't offer sponsorship. You can narrow results by location and role to focus on New Jersey's key employment centers like Jersey City, Newark, and Princeton. This saves significant time compared to manually researching each employer's sponsorship history.
Are there state-specific considerations for data managers seeking sponsorship in New Jersey?
New Jersey's dense concentration of pharmaceutical, financial services, and technology employers creates a competitive but active sponsorship market for data managers. The state's proximity to New York City means prevailing wage determinations often reflect metro-level rates, which employers must meet when filing Labor Condition Applications. Rutgers University and NJIT also produce a consistent pipeline of locally trained data professionals, so candidates with specialized experience in regulated industries like life sciences tend to stand out.
What is the prevailing wage for sponsored data manager jobs in New Jersey?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.