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Big Data Engineer Intern Jobs in Georgia (NOW HIRING)

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable ... The ideal candidate will bring strong expertise in cloud-based data processing, big data ...

Sr. Big Data Developer

Atlanta, GA · On-site

$51 - $66/hr

Years of Experience - 7+ Mandatory Skills - Java, Oracle, SQL , Green Plum Good Communication skill, Onsite experience Senior Big Data Technology Developer will be responsible for technically leading ...

Data Engineer - GCP

Atlanta, GA · On-site

$110K - $132K/yr

Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable ... The ideal candidate will bring strong expertise in cloud-based data processing, big data ...

Aws Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Qualifications (Data Engineer/Python Developer) 10+ years hands-on Python development experience for big data application. Extensive working experience in implementing scalable and efficient data ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... Big Data tools and technologies to code the data Engineering routines Designs and develops the Data Engineering routines for feature extraction, feature generation and feature engineering Works with ...

Engineer Intern

Covington, GA · On-site

$20.66/hr

The intern will work closely with the Chief Metallurgist and Quality Manager to support ongoing ... Reporting & Data AnalysisHelp stabilize and improve quality engineering reporting processes.Collect ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... and other Big Data tools and technologies to code the data Engineering routines • Designs and develops the Data Engineering routines for feature extraction, feature generation and feature ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Hands-on experience with big data frameworks: Apache Spark, Hive, Airflow, DatabricksExperience ... Microsoft Azure Data Engineer Associate or equivalent certifications preferred.Experience in data ...

New

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Hands-on experience with big data frameworks: Apache Spark, Hive, Airflow, DatabricksExperience ... Microsoft Azure Data Engineer Associate or equivalent certifications preferred.Experience in data ...

New

Showing results 21-40

Big Data Engineer Intern information

What does a Big Data Engineer Intern do?

A Big Data Engineer Intern assists with designing, building, and maintaining large-scale data processing systems. They often work with technologies such as Hadoop, Spark, and SQL to manage and analyze large datasets. Interns may help develop data pipelines, clean and organize data, and support senior engineers in optimizing data workflows. This role provides hands-on experience in handling big data tools and working on real-world data engineering projects.

What are the key skills and qualifications needed to thrive as a Big Data Engineer Intern?

To thrive as a Big Data Engineer Intern, you need a solid understanding of programming (especially Python, Java, or Scala), data structures, and basic knowledge of distributed computing concepts, typically supported by coursework or relevant projects. Familiarity with big data tools like Hadoop, Spark, and data querying languages such as SQL, as well as exposure to cloud platforms like AWS or Azure, is highly valuable. Strong analytical thinking, problem-solving abilities, and communication skills help interns collaborate effectively and learn quickly in dynamic environments. These skills and qualities are crucial for handling large-scale datasets and supporting the development of data-driven solutions within engineering teams.

What are some common challenges a Big Data Engineer Intern might face when working with large datasets?

As a Big Data Engineer Intern, you'll often encounter challenges related to managing the scale and complexity of massive datasets. These can include optimizing data ingestion pipelines for speed and efficiency, troubleshooting data quality issues, and ensuring data privacy and security. Additionally, you may need to quickly learn new tools or frameworks, such as Hadoop or Spark, and collaborate closely with data scientists and engineers to ensure data is structured and accessible for analysis. Developing problem-solving skills and being proactive in seeking help from your team can help you overcome these hurdles.

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

AspectBig Data Engineer InternData Engineer
CredentialsRelevant coursework, some internshipsBachelor's or master's in CS, experience preferred
Work EnvironmentInternship, learning-focused, entry-level projectsFull-time, professional projects, team collaboration
Industry UsageTech, finance, healthcare, startupsSame industries, more responsibility
Search & Comparison IntentEntry-level, internship opportunitiesCareer advancement, full-time roles

The main difference between a Big Data Engineer Intern and a Data Engineer is experience level and responsibility. Interns are typically students or early learners gaining exposure, while Data Engineers are full-time professionals managing complex data systems. Internships serve as stepping stones toward full-time data engineering careers.

What are the most commonly searched types of Big Data Engineer jobs in Georgia?

The most popular types of Big Data Engineer jobs in Georgia are:

Data Engineer - GCP

The Data Sherpas

Atlanta, GA • On-site, Remote

$110K - $132K/yr

Full-time

Medical, Dental, Vision

Re-posted 13 days ago


Job description

Who We Are:

We are a dynamic team focused on building innovative and scalable data solutions on Google Cloud Platform (GCP). Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable data pipelines and data infrastructure, ensuring data availability, accuracy, and performance for business insights and machine learning models.


What We Are Looking For:

We are seeking an experienced and highly skilled Google Cloud Data Engineer who will be responsible for developing and managing data pipelines on GCP. The ideal candidate will bring strong expertise in cloud-based data processing, big data technologies, and data modeling to help us provide high-performance data solutions.


Responsibilities:

Data Pipeline Development and Management:

  • Design, build, and maintain scalable and reliable data pipelines using Cloud Dataflow, Cloud Pub/Sub, and Cloud Composer.
  • Develop ETL/ELT processes to process and transform large volumes of structured and unstructured data.
  • Optimize data pipeline performance, scalability, and reliability.
  • Ensure data processing and ingestion workflows are monitored and meet performance SLAs.

Data Storage and Management:

  • Design and implement data storage solutions using BigQuery, Cloud Storage, and Firestore.
  • Optimize data structures and partitioning for performance and cost efficiency.
  • Ensure data security, integrity, and availability in all storage solutions.
  • Manage data lifecycle policies and archiving processes.

Data Transformation and Processing:

  • Develop data transformation processes using BigQuery, Apache Beam, and Cloud Functions.
  • Implement data quality checks, validation rules, and monitoring solutions.
  • Support real-time and batch data processing needs.

Data Integration and Automation:

  • Integrate data from multiple sources, including APIs, databases, and third-party applications.
  • Automate data ingestion, transformation, and export using tools like Cloud Composer and Cloud Functions.
  • Ensure data consistency across different environments and systems.

Collaboration and Stakeholder Engagement:

  • Work closely with data scientists and analysts to understand data needs and business goals.
  • Provide technical guidance and best practices to the data engineering and business teams.
  • Collaborate with security and compliance teams to ensure data governance standards are met.

Performance Monitoring and Troubleshooting:

  • Monitor data pipeline performance and troubleshoot issues in real-time.
  • Analyze data pipeline failures and implement fixes to prevent recurrence.
  • Set up logging and monitoring using Stackdriver and Cloud Monitoring.


Qualifications:

  • Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's degree is a plus.
  • 3+ years of experience in data engineering, with at least 2+ years working with Google Cloud Platform.
  • Google Professional Data Engineer certification is required.
  • Strong proficiency with GCP services such as BigQuery, Cloud Dataflow, Cloud Composer, Cloud Pub/Sub, Firestore, and Cloud Functions.
  • Hands-on experience with big data tools and frameworks such as Apache Beam, Hadoop, Spark, or Flink.
  • Hands-on experience with dbt.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Strong knowledge of SQL, data modeling, and query optimization.
  • Experience with CI/CD tools and version control (e.g., Git, Cloud Build).
  • Strong understanding of data governance, security, and compliance requirements.
  • Ability to manage large-scale data processing and real-time data pipelines.
  • Excellent problem-solving, analytical, and communication skills.
  • Must be a U.S. Citizen or Green Card holder.


Preferred Skills:

  • Experience with machine learning pipelines and AI/ML model deployment.
  • Familiarity with Terraform and Infrastructure as Code (IaC) principles.
  • Experience with NoSQL databases and key-value stores on GCP.
  • Knowledge of containerization and orchestration using Google Kubernetes Engine (GKE).


What We Offer:

  • Competitive salary and performance-based incentives.
  • Comprehensive health, dental, and vision coverage.
  • Professional development and training opportunities (including GCP certification).
  • Flexible work environment and remote work options.


Join us and be part of a team building innovative and scalable data solutions on Google Cloud Platform!


This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or Corp-to-Corp (C2C) arrangements. We are looking for the best talent and are flexible on the employment structure for the right candidate.


This position is open to direct candidates only. We are not working with third-party agencies.


Candidates must be U.S. Citizens or Green Card holders.