Clinical Data Specialist Jobs in Jersey City, NJ
Clinical Data Specialist jobs in Jersey City are concentrated in the life sciences and healthcare sectors anchored in the Newport and Harborside districts, with additional demand from financial services firms along the Hudson waterfront. Employers actively hiring include JPMorganChase, Citi, and Deloitte. See the openings below and apply to the ones that match your experience.
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Showing 5 of 104+ Clinical Data Specialist jobs
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank (CIB) – Regulatory Reporting Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems, with a focus on data engineering and Spark-based ETL/ELT
- Develops secure high-quality production code in Python/PySpark and Spark SQL, and reviews and debugs code written by others (Spark jobs, SQL logic, and data issues end-to-end)
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems, including data pipeline reliability and lakehouse maintenance automation
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture (e.g., EMR/Databricks, lakehouse/table formats, catalog/governance patterns)
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies, especially around Spark performance, Iceberg best practices, and data platform operations
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- 5+ years of applied experience building production data engineering and/or software engineering solutions (design, development, testing, operations)
- Hands-on practical experience delivering system design, application development, testing, and operational stability for large-scale data pipelines
- Advanced in one or more programming language(s), with advanced proficiency in Python and strong hands-on experience with PySpark.
- Advanced proficiency in Spark SQL and strong SQL fundamentals (data modeling, query optimization, execution plan analysis)
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs, outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practice
- Experience with AWS data management patterns including S3 and AWS Glue Data Catalog (metadata governance, table schema hygiene, discoverability). Would also consider other cloud based Data platform.
- Required platform experience: delivering and operating Spark workloads on EMR and or Databricks (tuning, troubleshooting, monitoring, and cost, performance optimization)
- Required lakehouse expertise: production experience with Apache Iceberg, including table design and ongoing operations such as partitioning strategy and file layout optimization, schema evolution and compatibility controls, compaction, small-file mitigation, snapshot retention management and metadata maintenance, safe backfills and rewrites, reprocessing patterns
- Proficiency in automation and continuous delivery methods (CI CD, automated testing, and repeatable deployments for data pipelines)
Preferred qualifications, capabilities, and skills
- Kafka familiarity (topic design, producer/consumer patterns, schema evolution/compatibility, and operational considerations) is a plus
- Experience with Delta Lake concepts and trade-offs vs. Iceberg
- Experience with Spark Structured Streaming and streaming ETL patterns
- Working knowledge of Java (interoperability or leveraging existing JVM-based components)
- Experience using AI-assisted engineering tools and workflows (e.g., GitHub Copilot, Claude) including spec-driven development, prompt-assisted refactoring, and code review—following enterprise-safe usage patterns
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank (CIB) – Regulatory Reporting Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems, with a focus on data engineering and Spark-based ETL/ELT
- Develops secure high-quality production code in Python/PySpark and Spark SQL, and reviews and debugs code written by others (Spark jobs, SQL logic, and data issues end-to-end)
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems, including data pipeline reliability and lakehouse maintenance automation
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture (e.g., EMR/Databricks, lakehouse/table formats, catalog/governance patterns)
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies, especially around Spark performance, Iceberg best practices, and data platform operations
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- 5+ years of applied experience building production data engineering and/or software engineering solutions (design, development, testing, operations)
- Hands-on practical experience delivering system design, application development, testing, and operational stability for large-scale data pipelines
- Advanced in one or more programming language(s), with advanced proficiency in Python and strong hands-on experience with PySpark.
- Advanced proficiency in Spark SQL and strong SQL fundamentals (data modeling, query optimization, execution plan analysis)
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs, outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practice
- Experience with AWS data management patterns including S3 and AWS Glue Data Catalog (metadata governance, table schema hygiene, discoverability). Would also consider other cloud based Data platform.
- Required platform experience: delivering and operating Spark workloads on EMR and or Databricks (tuning, troubleshooting, monitoring, and cost, performance optimization)
- Required lakehouse expertise: production experience with Apache Iceberg, including table design and ongoing operations such as partitioning strategy and file layout optimization, schema evolution and compatibility controls, compaction, small-file mitigation, snapshot retention management and metadata maintenance, safe backfills and rewrites, reprocessing patterns
- Proficiency in automation and continuous delivery methods (CI CD, automated testing, and repeatable deployments for data pipelines)
Preferred qualifications, capabilities, and skills
- Kafka familiarity (topic design, producer/consumer patterns, schema evolution/compatibility, and operational considerations) is a plus
- Experience with Delta Lake concepts and trade-offs vs. Iceberg
- Experience with Spark Structured Streaming and streaming ETL patterns
- Working knowledge of Java (interoperability or leveraging existing JVM-based components)
- Experience using AI-assisted engineering tools and workflows (e.g., GitHub Copilot, Claude) including spec-driven development, prompt-assisted refactoring, and code review—following enterprise-safe usage patterns
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
See All 104+ Clinical Data Specialist Jobs in Jersey City
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Find Clinical Data Specialist JobsClinical Data Specialist Job Market in Jersey City
Who's Hiring
- JPMorganChase37
- Citi10
- Deloitte4
- Amazon Web Services4
- Tata Consultancy Services (TCS)4
Top Industries Hiring
- Investment & Asset Management30
- Banking & Financial Services29
- Technology & Software21
- Fintech19
- Construction & Real Estate6
Clinical Data Specialist Jobs in Jersey City: Frequently Asked Questions
How do I get a clinical data specialist job in Jersey City?
Focus your search on Jersey City's Newport and Harborside districts, where contract research organizations, hospital systems, and pharmaceutical companies concentrate most of their data operations. Candidates with hands-on experience in EDC platforms, CDISC standards, or regulatory data submissions stand out in this market. Proximity to the broader New York City metro also means many Jersey City employers expect candidates familiar with fast-paced, multi-study environments.
Which companies hire clinical data specialists in Jersey City?
Companies currently hiring clinical data specialists in Jersey City include JPMorganChase, Citi, and Deloitte, per current listings on Migrate Mate as of July 2026. Jersey City's employer mix leans toward mid-size contract research organizations and regional hospital networks that maintain dedicated clinical data teams for ongoing trials and regulatory submissions.
Are there remote clinical data specialist jobs in Jersey City?
Yes, though availability depends on the role's function: desk-based tasks like data entry review, query management, and reporting tend to be remote-friendly, while site coordination or hands-on data collection roles typically require in-person presence. About 24% of clinical data specialist openings tied to Jersey City are remote or hybrid as of July 2026. Fully remote postings in Jersey City most often come from larger CROs and pharmaceutical operations teams.
How can I get a clinical data specialist job in Jersey City with little or no experience?
The most realistic entry path in Jersey City is through data coordinator or clinical research associate roles at local contract research organizations and hospital systems, which routinely hire candidates still building their credentials. Entry-level openings at Jersey City's mid-size CROs often value familiarity with EDC tools like Medidata Rave or REDCap over years of direct experience. Volunteering or interning with a local academic medical center affiliated with the Hudson County network can also open doors to paid clinical data roles.
Which industries hire the most clinical data specialists in Jersey City?
Jersey City clinical data specialist roles concentrate in Investment & Asset Management, Banking & Financial Services, and Technology & Software, based on current listings on Migrate Mate as of July 2026. Jersey City's position as a logistics and corporate hub adjacent to major New York City medical and research institutions draws both pharma back-office operations and regional hospital data teams to the area.
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