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Big Data Infrastructure Engineer Jobs in Florida

KBR

Big Data Systems Engineer

Tampa, FL · Hybrid

Big Data Systems Engineer Belong, Connect, Grow, with KBR! KBR's National Security Solutions (NSS ... big data infrastructure. * Must have strong troubleshooting skills and the ability to become a ...

KBR, Inc.

Big Data Systems Engineer

Niceville, FL · On-site

Big Data Systems Engineer Belong, Connect, Grow, with KBR! KBR's National Security Solutions (NSS ... big data infrastructure. * Must have strong troubleshooting skills and the ability to become a ...

KBR

Big Data Systems Engineer

Niceville, FL · Hybrid

Big Data Systems Engineer Belong, Connect, Grow, with KBR! KBR's National Security Solutions (NSS ... big data infrastructure. * Must have strong troubleshooting skills and the ability to become a ...

Professional Staffing Services

Data Engineer

Orlando, FL · Hybrid

$50 - $65/hr

In this role, you will design, build, and optimize scalable data infrastructure to support complex ... Tune ETL jobs and SQL queries for maximum performance and scalability to seamlessly handle big data ...

krg technology inc

Big Data Architect

Fort Myers, FL · On-site

$59.50 - $76.50/hr

... engineer and architect across domains Past hands on experience with open source Big data ... subsequent infrastructure tuning for a major Big Data project Additional Information Strong ...

KLANIK

Data Engineer

Miami, FL · On-site

$110K - $133K/yr

... Big Data & AI. We are looking for a Data Engineer to design, build, and maintain a scalable and ... data infrastructure needs Document pipelines, data models, and technical processes Mentor team ...

Leidos

Data Center Infrastructure Engineer

Orlando, FL · On-site

$100K - $131K/yr

Leidos has a new and exciting opportunity for a Data Center Infrastructure Engineer in our Cyber ... Experience with F5 / BIG IP physical and virtual network devices. Ability to solve technical ...

Leidos

Data Center Infrastructure Engineer

Orlando, FL · On-site

$100K - $131K/yr

Leidos has a new and exciting opportunity for a Data Center Infrastructure Engineer in our Cyber ... Experience with F5 / BIG IP physical and virtual network devices. Ability to solve technical ...

Vultus Inc

Data Engineer

Palm Coast, FL · On-site

$100K - $121K/yr

... infrastructure. The ideal candidate should have experience working with large datasets, cloud ... Work with cloud-based data platforms and big data technologies. Monitor, troubleshoot, and resolve ...

Mindlance

Big Data Lead

Tampa, FL · On-site

They are seeking a Big Data Lead with experience in Big Data technologies, particularly in the ... Responsibilities : • Looking for a Developer / Support resource with experience in BigData ...

Kforce Technology Staffing

Data Engineer

Miami, FL · On-site

$109K - $131K/yr

Design, implement and support an analytical data infrastructure and working knowledge of Modern ... Knowledge of big data technologies, including Hadoop, Spark, Kafka, and HBase, with experience in ...

Citi

Senior Java Big Data Developer

Tampa, FL · On-site

$113K - $170K/yr

Citi is looking for a Senior JAVA Big Data Developer to design, build, and scale high-performance ... Infrastructure & Platform Knowledge: Solid understanding of container orchestration concepts ...

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Big Data Infrastructure Engineer information

What is a big data infrastructure engineer?

Big Data Infrastructure Engineers are IT professionals responsible for designing, building, and maintaining the systems and environments that process and store large volumes of data. They work with technologies such as Hadoop, Spark, and cloud platforms to ensure data pipelines are efficient, scalable, and reliable. These engineers also manage data storage, security, and high-performance computing resources, enabling organizations to analyze and leverage big data for business insights.

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

To thrive as a Big Data Infrastructure Engineer, you need expertise in distributed systems, data architecture, and programming languages like Java, Scala, or Python, typically backed by a relevant degree in computer science or engineering. Proficiency with big data tools such as Hadoop, Spark, Kafka, and experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies are crucial, as are certifications in these areas. Strong problem-solving, teamwork, and communication skills set top performers apart in this role. These skills enable efficient design, deployment, and maintenance of scalable data systems that support business intelligence and analytics needs.

What are some common challenges big data infrastructure engineers face when ensuring system scalability and reliability?

Big Data Infrastructure Engineers often encounter challenges related to optimizing system performance as data volumes grow rapidly. Ensuring that the infrastructure can scale horizontally without downtime requires careful planning and implementation of distributed computing frameworks. Additionally, maintaining data integrity and fault tolerance in complex, multi-node environments can be demanding, requiring constant monitoring and quick responses to system failures. Collaborating closely with data engineers and DevOps teams is essential to proactively address these challenges and implement robust solutions.

What is the difference between Big Data Infrastructure Engineer vs Data Engineer?

AspectBig Data Infrastructure EngineerData Engineer
Primary FocusDesigning, building, and maintaining big data infrastructure and pipelinesDeveloping and managing data pipelines, databases, and data models
Skills & CertificationsHadoop, Spark, cloud platforms, Linux, scriptingSQL, Python, ETL tools, cloud services
Work EnvironmentData centers, cloud environments, big data platformsData warehouses, cloud platforms, analytics teams
Industry UsageTech, finance, healthcare, any data-heavy industryTech, finance, retail, analytics-focused companies

While both roles involve working with data, Big Data Infrastructure Engineers focus on building and maintaining the infrastructure for processing large datasets, whereas Data Engineers develop data pipelines and models to enable data analysis. Understanding these distinctions helps in choosing the right career path or job search focus.

Big Data Engineer

Tampa, FL • On-site

Ruri Software Technologies LLC
Software Development • 11 - 50 employees
Learn more about Ruri Software Technologies LLCexternal

$52.75 - $69.75/hr

Full-time

Re-posted 24 days ago

Job description

Big Data Engineer
City :Tampa
State :FL
Job Description :
TOP REQUIREMENTS:
Big Data (Spark, Scala, Hive, Hadoop Ecosystem)
Data Streaming (Kafka)
Responsibilities
  • Building and supporting a cloud based analytical platform for complex data systems.
  • Document technical applications, specifications, and enhancements.
  • Collaborate with business and technical stakeholders while defining solutions.
  • Collaborate with the data scientists to organize huge sets of data for data modeling.
  • Recommend ways to improve data reliability, quality and efficiency.
  • Lead engineers in making sound, sustainable, and practical technical decisions.
  • Foster high-performance, collaborative technical work resulting in high-quality output.
  • Compile and present key findings and reports to all levels of the organization, including senior leadership.

What skills/attributes are a must have?
  • 5+ years of experience with Big Data (HDFS, MapReduce, Hive, HBase, Pig, Sqoop, Spark, Scala).
  • Experience building and optimizing data pipelines, architectures and data sets.
  • Experience with data modelling, data management and ETL tools like Kafka Connect, Informatica etc.
  • Experience building and deploying applications to the cloud (AWS, Azure, etc.).
  • Experience working in an Agile environment.
  • Expertise with modern programming languages, systems, and architectures.

What skills/attributes are nice to have?
  • BA/BS degree in Computer Science or equivalent experience.
  • Experience with the use of containers such as Kubernetes and Docker.
  • Experience with DevOps, Continuous Integration, and Continuous Delivery.
  • Expertise in performance and scalability optimization.
  • Knowledge of software and infrastructure security practices.

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