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Java Data Engineer Jobs in Deer Park, NY (NOW HIRING)

... Java, Scala, or similar programming languages. Advanced SQL expertise, including performance tuning and optimization across large datasets. - Deep experience with Apache Spark and cloud-native big ...

Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake * Share your passion for ...

Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake * Share your passion for ...

Senior Data Engineer

New York, NY · On-site

$62K - $72K/yr

Snowflake Data Engineering, Streams Tasks, Dynamic Tables, Snowpipe & Advanced SQL. Required ... SQL Java Integration: Strong proficiency in complex SQL window functions CTEs merge statements and ...

Lead Data Engineer (Bank Tech)

New York, NY · On-site

$112K - $147K/yr

Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake * Share your passion for ...

Lead Data Engineer (Bank Tech)

New York, NY · On-site

$112K - $147K/yr

Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake * Share your passion for ...

Data Engineer - New York

New York, NY · On-site

$125K - $150K/yr

Experience with high-throughput, low-latency programming in C#, F#, C++, or Java is a plus. * Advanced SQL skills and experience with modern data storage and querying technologies such as Snowflake ...

Data Engineer - New York

New York, NY · On-site

$125K - $150K/yr

Experience with high-throughput, low-latency programming in C#, F#, C++, or Java is a plus. * Advanced SQL skills and experience with modern data storage and querying technologies such as Snowflake ...

Healthcare Data Engineer

New York, NY · Remote

$117K - $140K/yr

Proficiency in SQL, PL/SQL, T-SQL, Hadoop, Python, and Java. Optimization: Hands-on experience in ... Data Operations: Experience with ETL processes and QA within a SQL environment. Experience ...

Data Engineer, Data Foundations

New York, NY · On-site

$125K - $150K/yr

Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their ... Knowledge of Java or Golang (nice to have) * Experience with Kubernetes (nice to have) * Genuine ...

Proficiency in SQL and experience with scripting languages such as Python, Java, or Scala ... Data Engineer". Please note that we are unable to respond to general status inquiries or other ...

Sr. Data Engineer I

New York, NY · On-site

$116K - $157K/yr

Senior Data Engineer I - Scibids Role: Senior Data Engineer I - Scibids Location: New York, NY ... You have strong programming skills in Python and SQL; experience with Java, Rust, or similar ...

Java Engineer (Multicast)

New York, NY

$56.50 - $77.75/hr

Java Engineer (Multicast) Location: New York, NY Type: Direct Hire Client located in New York, New ... This position reports to the VP of Data Services and participates on a four person team of ...

Showing results 41-60

Java Data Engineer information

See Deer Park, NY salary details

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How much do java data engineer jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for java data engineer in Deer Park, NY is $62.84, according to ZipRecruiter salary data. Most workers in this role earn between $51.73 and $71.01 per hour, depending on experience, location, and employer.

What is a Java data engineer?

A Java Data Engineer is a technology professional who designs, develops, and maintains data processing systems using Java programming language. They work with large datasets, build data pipelines, and ensure the efficient movement, transformation, and storage of data. Java Data Engineers often collaborate with data scientists, analysts, and other engineers to support data-driven decision-making in organizations. Their expertise typically includes Java, SQL, big data technologies like Hadoop or Spark, and cloud platforms. They play a crucial role in enabling reliable and scalable data infrastructure for businesses.

What are the key skills and qualifications needed to thrive as a Java data engineer?

To thrive as a Java Data Engineer, you need strong programming skills in Java, a solid understanding of data structures, SQL, and experience with big data frameworks, often supported by a degree in computer science or a related field. Familiarity with data processing tools like Apache Spark, Hadoop, Kafka, and experience with cloud data platforms (e.g., AWS, GCP) or relevant certifications are typically required. Analytical thinking, problem-solving ability, and effective communication are crucial soft skills for collaborating with teams and interpreting data requirements. These capabilities are essential for building reliable, scalable data solutions that support business intelligence and analytics needs.

What are the most common challenges faced by Java data engineers when working with large-scale data pipelines?

Java Data Engineers often encounter challenges with optimizing the performance and scalability of data pipelines, especially as data volumes grow. They must ensure data integrity and consistency while managing distributed systems and integrating with various data sources. Debugging issues in real-time data processing and maintaining efficient, fault-tolerant code are also key hurdles. Collaborating closely with data scientists, database administrators, and DevOps teams is essential to overcome these challenges and deliver reliable data solutions.

What is the difference between Java Data Engineer vs Python Data Engineer?

AspectJava Data EngineerPython Data Engineer
Required CredentialsBachelor's in Computer Science, Java certificationsBachelor's in Computer Science, Python certifications
Work EnvironmentBig data platforms, Java-based toolsData analysis, scripting, Python-based tools
Employer & Industry UsageFinancial services, enterprise systemsTech startups, data science projects
Common Search & ComparisonYesYes

Java Data Engineers and Python Data Engineers often share similar roles in data processing and engineering. The main difference lies in the programming languages used: Java is common in large-scale enterprise environments, while Python is favored for data analysis and scripting. Both roles require strong programming skills, but their toolsets and typical applications differ based on industry needs.

What are popular job titles related to Java Data Engineer jobs in Deer Park, NY?

For Java Data Engineer jobs in Deer Park, NY, the most frequently searched job titles are:

What job categories do people searching Java Data Engineer jobs in Deer Park, NY look for?

The top searched job categories for Java Data Engineer jobs in Deer Park, NY are:

What cities near Deer Park, NY are hiring for Java Data Engineer jobs?

Cities near Deer Park, NY with the most Java Data Engineer job openings:

Staff Data Engineer- Data Lake

H1

New York, NY • On-site

Full-time

Medical, Life, Retirement, PTO

Re-posted 25 days ago


Job description

At H1, we believe access to the best healthcare information is a basic human right. Our mission is to provide a platform that can optimally inform every doctor interaction globally. This promotes health equity and builds needed trust in healthcare systems. To accomplish this, our teams harness the power of data and AI technology to unlock groundbreaking medical insights and convert those insights into actions that result in optimal patient outcomes and accelerate an equitable and inclusive drug development lifecycle. Visit h1.co to learn more about us.
Data Engineering is responsible for the development and delivery of our most important asset-our data. With thousands of data sources from around the world, the team ensures that data is accurate, normalized, and delivered at a velocity that keeps up with real-world changes. As we expand our markets and the scope of data we provide to our customers, our team must scale to meet that demand.
WHAT YOU'LL DO AT H1
As a Staff Data Engineer on the Data Lake team at H1, you will play a critical role in shaping the architecture, scalability, reliability, and long-term direction of our core data platform. This role is designed for a highly technical engineer who is excited to grow into an Engineering Manager track while remaining deeply hands-on technically.
The Data Lake is the foundation of H1's platform, responsible for the validation, accuracy, standardization, and quality of the data powering every downstream product and team across the organization. You will help lead the evolution of this platform while supporting and mentoring a growing team of engineers.
You will:
- Architect, build, and scale distributed ETL/ELT pipelines and large-scale ingestion frameworks across structured and unstructured healthcare datasets.
- Lead the evolution of H1's Data Lake architecture with a focus on scalability, observability, reliability, and cost optimization.
- Own and improve data quality, validation, normalization, and standardization workflows across thousands of global data sources.
- Design and optimize batch and near real-time data processing frameworks using cloud-native distributed systems.
- Optimize distributed compute and storage systems, including Spark workloads, query performance, partitioning strategies, and infrastructure efficiency.
- Drive improvements in monitoring, governance, operational excellence, and production reliability across the platform.
- Troubleshoot complex production data and infrastructure issues across distributed systems.
- Partner closely with Product, Infrastructure, Security, Compliance, and downstream engineering teams to support scalable and secure data delivery.
- Mentor engineers through technical leadership, architecture reviews, and engineering best practices.
- Help define technical roadmap priorities and contribute to long-term platform strategy and execution planning.
- Support production operations, incident response, and platform health as part of overall ownership of the Data Lake ecosystem.
ABOUT YOU
You are a highly technical data engineer who thrives in lean, high-ownership environments and enjoys solving complex distributed systems challenges. You are excited by the opportunity to influence technical direction, mentor engineers, and grow into broader engineering leadership responsibilities while remaining hands-on.
- You have deep experience designing and scaling distributed data platforms and large-scale pipelines in cloud-native environments.
- You excel at building reliable, observable, and maintainable data systems supporting critical business and analytics workloads.
- You have strong expertise in distributed processing, performance optimization, and modern data architecture patterns.
- You are comfortable leading technical initiatives and influencing architecture decisions across teams.
- You communicate effectively with both technical and non-technical stakeholders.
- You enjoy mentoring engineers and helping raise the engineering bar across teams.
- You are energized by ownership, autonomy, and solving ambiguous technical challenges.
REQUIREMENTS
- 8+ years of experience in data engineering, software engineering, or related fields with significant experience building and scaling distributed data platforms.
- Demonstrated technical leadership experience with interest in or experience mentoring and leading engineers.
- Strong proficiency in Python (PySpark), Java, Scala, or similar programming languages.
Advanced SQL expertise, including performance tuning and optimization across large datasets.
- Deep experience with Apache Spark and cloud-native big data platforms, preferably within AWS environments (EMR, Glue, S3, Athena, Redshift, or similar).
- Experience designing and scaling modern cloud-native data lake architectures and large-scale ingestion frameworks.
- Experience with orchestration and workflow management tools such as Argo, Airflow, or similar technologies.
- Strong understanding of distributed storage systems, partitioning strategies, and file formats such as Parquet, Avro, and ORC.
- Experience with Docker, Kubernetes, and modern containerization technologies.
- Experience implementing monitoring, observability, and data quality frameworks within production environments.
- Experience with large-scale data cleaning, parsing, normalization, and validation workflows preferred.
- Experience working with healthcare, life sciences, publication, or large-scale entity-resolution datasets preferred.
- Exposure to ML/AI-driven data enrichment, parsing, or validation workflows is a plus.
- Experience using AI-assisted coding tools (e.g., GitHub Copilot, Claude Code) to accelerate development while maintaining quality is encouraged
COMPENSATION
This role pays $190,000 to $220,000 per year, based on experience, in addition to stock options.
Anticipated role close date: 9/15/2026
H1 OFFERS
- Full suite of health insurance options, in addition to generous paid time off
- Pre-planned company-wide wellness holidays
- Retirement options
- Health & charitable donation stipends
- Impactful Business Resource Groups
- Flexible work hours & the opportunity to work from anywhere
- The opportunity to work with leading biotech and life sciences companies in an innovative industry with a mission to improve healthcare around the globe
H1 is proud to be an equal opportunity employer that celebrates diversity and is committed to creating an inclusive workplace with equal opportunity for all applicants and teammates. Our goal is to recruit the most talented people from a diverse candidate pool regardless of race, color, ancestry, national origin, religion, disability, sex (including pregnancy), age, gender, gender identity, sexual orientation, marital status, veteran status, or any other characteristic protected by law.
H1 is committed to working with and providing access and reasonable accommodation to applicants with mental and/or physical disabilities. If you require an accommodation, please reach out to your recruiter once you've begun the interview process. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

H1 logo

About H1

Sourced by ZipRecruiter

Industry

Software development

Company size

201 - 500 Employees

Headquarters location

New York, NY, US

Year founded

2017