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Big Data Engg Jobs in Arkansas

Bhjob15656_20166 - Head Architect - Big Data Asic
By Myticas Consulting At United States
Be able to understand both internal and external customer requirements and translate them into technical solutions
At least 8 years of experience and a proven track record of optimally delivering many complex RTL designs targeting large FPGAs/ASICs
Expertise in VHDL/Verilog or similar with additional coding experience in C, C++ or similar low-level languages
Strong communication, presentation and collaboration skills to lead a global team and leverage resources from the industry and academy
Be able to lead the architecture design of new computing infrastructure and ASIC chips for data-intensive application
Be able to generate insights from the industry and academic trends of big data analytics, and propose technical strategy and roadmap
Data Analyst/Big Data Associate Educator
By Swelar At United States
Compensation will depend on your education, experience, skills, abilities, and market trends.
Write and research new content to keep teaching skills up-to-date
Use Swelar’s Agile methodology to continuously enhance students' learning experiences
Strong skills in SQL, R, python, and visualization tools
Experience in numerical and categorical modelling techniques and various machine learning methods
Experience in designing and applying data science experiments using various tools and methods
Deep Tech, Ai, And Big Data Engineers
By Traverse Ventures Studio At United States
Experience with big data technologies and frameworks, such as Hadoop, Spark, or TensorFlow.
Strong problem-solving skills and the ability to think creatively to devise innovative solutions.
Excellent communication skills and the ability to collaborate effectively in a multidisciplinary team.
To be successful in this role, you should possess the following qualifications:
Collaborating with a multidisciplinary team of scientists, engineers, and researchers to design and implement data-driven approaches, novel processes, or systems-level solutions.
Applying artificial intelligence and machine learning techniques to analyze large datasets and extract meaningful insights.
Big Data Admin Jobs
By InfoGravity At United States
Collaborate with cross-functional teams to understand data requirements and provide technical support.
Proven experience as a Big Data Administrator managing large-scale environments.
In-depth knowledge of Hadoop, Spark, Hive, and related tools.
Experience in performance tuning and troubleshooting of big data systems.
Excellent problem-solving and communication skills.
Deploy, configure, and maintain the organization's big data infrastructure (Hadoop, Spark, etc.).
Big Data Analyst Jobs
By DIRECTV At United States
Must have excellent organizational, analytical, and time management skills
Tell the story using data behind our most critical customer experiences by:
Drilling to the root cause through analysis and business knowledge
3-5 years of related experience in advanced analytics, data science, big data, relational database structures, reporting, dashboarding, ad hoc analysis
Strong oral, written and interpersonal communication skills, must be capable of explaining complex information to others in straightforward manner
Gathers, analyzes, and interprets a wide variety of data to identify causal relationships and trigger points that influence customer behavior.

Are you looking for an exciting opportunity to work with Big Data? We are looking for a Big Data Engineer to join our team and help us develop and maintain our data infrastructure. You will be responsible for designing, developing, and maintaining data pipelines, data warehouses, and data lakes. You will also be responsible for developing and optimizing data models and ETL processes. If you have a passion for data and a desire to work with cutting-edge technologies, this is the job for you!

Overview A Big Data Engineer is responsible for designing, developing, and managing the architecture of large-scale data processing systems. They are responsible for the development of data pipelines and data storage solutions, as well as the integration of data from multiple sources. They must be able to analyze data and develop algorithms to process it. Detailed Job Description A Big Data Engineer is responsible for designing, developing, and managing the architecture of large-scale data processing systems. They must be able to analyze data and develop algorithms to process it. They must be able to design and develop data pipelines and data storage solutions, as well as the integration of data from multiple sources. They must be able to develop and maintain data models and data warehouses. They must also be able to develop and maintain data security and privacy policies. Job Skills Required
• Knowledge of big data technologies such as Hadoop, Spark, Kafka, and NoSQL databases
• Knowledge of data warehousing and data modeling
• Knowledge of data security and privacy policies
• Knowledge of data integration techniques
• Knowledge of data mining and machine learning algorithms
• Knowledge of scripting languages such as Python and R
• Knowledge of cloud computing technologies
• Ability to analyze and interpret data
• Ability to design and develop data pipelines
• Ability to troubleshoot and debug data processing systems
• Ability to work independently and in a team environment
Job Qualifications
• Bachelor’s degree in Computer Science, Information Technology, or a related field
• 5+ years of experience in data engineering or a related field
• Experience with big data technologies such as Hadoop, Spark, Kafka, and NoSQL databases
• Experience with data warehousing and data modeling
• Experience with data security and privacy policies
• Experience with data integration techniques
• Experience with data mining and machine learning algorithms
• Experience with scripting languages such as Python and R
• Experience with cloud computing technologies
• Strong analytical and problem-solving skills
• Excellent communication and interpersonal skills
Job Knowledge
• Knowledge of big data technologies such as Hadoop, Spark, Kafka, and NoSQL databases
• Knowledge of data warehousing and data modeling
• Knowledge of data security and privacy policies
• Knowledge of data integration techniques
• Knowledge of data mining and machine learning algorithms
• Knowledge of scripting languages such as Python and R
• Knowledge of cloud computing technologies
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