Data Parallelism developer

A Data Parallelism developer designs and implements software solutions that allow tasks to be split and run simultaneously across multiple processors or computing nodes. They leverage data parallelism to speed up processing times for large datasets. This involves partitioning data into smaller chunks, distributing it across various computing resources, and running computations in parallel. They are also responsible for ensuring data consistency and managing communication between processors. Understanding of parallel computing architectures, multi-threading, and synchronization is crucial. They often work with big data technologies and need to be proficient in programming languages like Python, Java, or C++.

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Data Parallelism developer

Hiring a Data Parallelism developer is essential for optimizing computational tasks, especially in handling large volumes of data. They can significantly speed up processing time by breaking down tasks and distributing them across multiple processors. This parallelization not only enhances efficiency, but also improves the performance of machine learning algorithms, data analysis, and complex calculations. Their expertise can help your organization to process big data faster, make timely decisions, and gain a competitive edge in the data-driven market.

Luke Zuze

IT/Programming

Data Parallelism,

Tableau,

SQL,

Ssas,

SSIS,

Kafka,

Spark

Stan Slutsky

IT/Programming

Data Parallelism,

Scrum Master,

QA Management,

IT-consulting,

IT Management,

IT Service Management,

WinSCP,

MS SQL Server,

SQL,

PL/SQL,

Asm,

Jira,

unix,

Big data,

AWS,

Certified Information Systems Security Professional (CISSP),

PowerBuilder,

Citrix,

ETL,

Computer Science,

HP-UX Administration,

Data Scientists,

Exchange,

Tableau,

SoapUI,

Google Cloud Datastore,

CRM,

Data architecture,

Selenium,

BizTalk Server,

Agile,

Toad,

Waterfall,

Ibm websphere,

IBM Db2,

SAS,

Mathematics,

SQL query,

J2EE,

SDLC,

SSH,

Windows,

Python,

Active Directory,

AIX,

SharePoint

Andrey Bulgakov

IT/Programming

Data Parallelism,

ASP.NET,

Selenium WebDriver,

PostgreSQL,

DevExpress,

.NET Framework,

C#,

.NET

Dmitry Shkadarevich

IT/Programming

Data Parallelism,

Deep Learning,

Computer Vision,

C++,

Python

Michael Scott

IT/Programming

Data Parallelism,

SQL,

Software Development,

Oracle,

Database Developer,

unix

Aigerim Kurmanalieva

IT/Programming

Data Parallelism,

AQA,

QA,

Java,

SQL,

Selenide,

Cucumber,

Postman,

Singleton,

Jenkins,

Maven,

JUnit,

TestNG,

Git,

GitHub,

MySQL,

PostgreSQL

Luke Zuze

IT/Programming

Data Parallelism,

Tableau,

SQL,

Ssas,

SSIS,

Kafka,

Spark

Stan Slutsky

IT/Programming

Data Parallelism,

Scrum Master,

QA Management,

IT-consulting,

IT Management,

IT Service Management,

WinSCP,

MS SQL Server,

SQL,

PL/SQL,

Asm,

Jira,

unix,

Big data,

AWS,

Certified Information Systems Security Professional (CISSP),

PowerBuilder,

Citrix,

ETL,

Computer Science,

HP-UX Administration,

Data Scientists,

Exchange,

Tableau,

SoapUI,

Google Cloud Datastore,

CRM,

Data architecture,

Selenium,

BizTalk Server,

Agile,

Toad,

Waterfall,

Ibm websphere,

IBM Db2,

SAS,

Mathematics,

SQL query,

J2EE,

SDLC,

SSH,

Windows,

Python,

Active Directory,

AIX,

SharePoint

Andrey Bulgakov

IT/Programming

Data Parallelism,

ASP.NET,

Selenium WebDriver,

PostgreSQL,

DevExpress,

.NET Framework,

C#,

.NET

Dmitry Shkadarevich

IT/Programming

Data Parallelism,

Deep Learning,

Computer Vision,

C++,

Python

Michael Scott

IT/Programming

Data Parallelism,

SQL,

Software Development,

Oracle,

Database Developer,

unix

Aigerim Kurmanalieva

IT/Programming

Data Parallelism,

AQA,

QA,

Java,

SQL,

Selenide,

Cucumber,

Postman,

Singleton,

Jenkins,

Maven,

JUnit,

TestNG,

Git,

GitHub,

MySQL,

PostgreSQL

Luke Zuze

IT/Programming

Data Parallelism,

Tableau,

SQL,

Ssas,

SSIS,

Kafka,

Spark

Stan Slutsky

IT/Programming

Data Parallelism,

Scrum Master,

QA Management,

IT-consulting,

IT Management,

IT Service Management,

WinSCP,

MS SQL Server,

SQL,

PL/SQL,

Asm,

Jira,

unix,

Big data,

AWS,

Certified Information Systems Security Professional (CISSP),

PowerBuilder,

Citrix,

ETL,

Computer Science,

HP-UX Administration,

Data Scientists,

Exchange,

Tableau,

SoapUI,

Google Cloud Datastore,

CRM,

Data architecture,

Selenium,

BizTalk Server,

Agile,

Toad,

Waterfall,

Ibm websphere,

IBM Db2,

SAS,

Mathematics,

SQL query,

J2EE,

SDLC,

SSH,

Windows,

Python,

Active Directory,

AIX,

SharePoint

Andrey Bulgakov

IT/Programming

Data Parallelism,

ASP.NET,

Selenium WebDriver,

PostgreSQL,

DevExpress,

.NET Framework,

C#,

.NET

Dmitry Shkadarevich

IT/Programming

Data Parallelism,

Deep Learning,

Computer Vision,

C++,

Python

Michael Scott

IT/Programming

Data Parallelism,

SQL,

Software Development,

Oracle,

Database Developer,

unix

Data Parallelism developers are instrumental in improving the efficiency and speed of data processing in large-scale computing environments. They specialize in dividing large datasets and processing them concurrently, which significantly reduces the time taken to analyze and interpret data.

One major advantage of hiring a Data Parallelism developer is their ability to streamline data processing tasks. They can design and implement parallel algorithms that allow simultaneous processing of data, drastically reducing the overall computing time. This is particularly beneficial for companies that handle large volumes of data and require quick insights.

Another advantage is their ability to optimize resource usage. By distributing data and tasks across multiple processors, they ensure optimal utilization of system resources. This not only enhances system performance but also reduces operational costs associated with data processing.

Data Parallelism developers also contribute to improved scalability. Their expertise allows businesses to add more processors to handle increased data loads without impacting the system's performance. This scalability is crucial for businesses that anticipate data growth.

Moreover, these developers have a deep understanding of complex data structures and parallel computing architectures. Their skills are vital in troubleshooting and resolving any issues that might arise during data processing, ensuring smooth and uninterrupted operations.

In conclusion, hiring a Data Parallelism developer can significantly enhance data processing speed, optimize resources, improve scalability, and ensure seamless operations in a data-intensive business environment.

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