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Big Data Engineer Intern Jobs in Georgia (NOW HIRING)

Data Engineer, Analytics

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, Analytics

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 science engineer

Alpharetta, GA · On-site

$108K - $130K/yr

Amazon Web Services, Google Cloud, Microsoft • Experience with big data technologies: Apache Spark, Hadoop, Kafka • Familiarity with data warehousing concepts • Understanding of CI/CD and DevOp ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Details: Data Engineer Location: Berkeley Heights, NJ/Atlanta, GA (Hybrid) Duration: 6 months ... Big Data experience with Snowflake, Greenplum, Netezza, or Teradata Desired Skills * Experience ...

Senior Data Engineer

Atlanta, GA · On-site

$101K - $138K/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

Senior Data Engineer

Atlanta, GA · On-site

$101K - $138K/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

Senior data engineer

Alpharetta, GA · On-site

$100K - $136K/yr

Amazon Web Services, Google Cloud, Microsoft • Experience with big data technologies: Apache Spark, Hadoop, Kafka • Familiarity with data warehousing concepts • Understanding of CI/CD and DevOp ...

Showing results 41-60

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, Analytics

4P Consulting Inc

Atlanta, GA • On-site

$110K - $132K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Senior Data EngineerLocation: Atlanta, GAClient- Southern CompanyContract- 1 YearExperience Level: 10+ YearsPosition Summary:We are seeking an experienced Senior Data Engineer with a strong background in designing and developing robust, scalable, and high-performance data infrastructure. The ideal candidate will have 10+ years of experience in manipulating data, working with both relational and NoSQL systems, and building modern data pipelines across data lakes and warehouses. This role demands a deep technical skillset in SQL, data modeling, and data pipeline orchestration tools like Apache Spark, Hive, and Airflow.Key Responsibilities:Design, develop, and maintain scalable ETL/ELT pipelines to process and integrate data from disparate sources.Work with structured and unstructured data to build clean, efficient, and machine-readable datasets.Normalize databases and ensure that data structures align with application and business requirements.Collaborate with business analysts, data scientists, and software engineers to deliver data solutions aligned with company objectives.Design and implement data models that support reporting, analytics, and machine learning use cases.Migrate and optimize workloads in cloud-based environments (e.g., Azure, AWS, GCP).Monitor and optimize data pipeline performance, data quality, and reliability.Implement data governance best practices and ensure compliance with security and privacy regulations.Technical Skills & Expertise:Expert-level proficiency in SQL, including writing complex queries and optimizing performance.Deep understanding of data modeling techniques for both OLTP and OLAP systems.Hands-on experience with big data frameworks: Apache Spark, Hive, Airflow, DatabricksExperience with modern cloud data platforms: Azure Data Lake, Azure Synapse, AWS Redshift, or Google BigQueryStrong experience with data orchestration, scheduling, and automation tools.Familiarity with Python, Scala, or Java for data processing and scripting tasks.Knowledge of NoSQL databases (e.g., MongoDB, Cassandra) and streaming tools (e.g., Kafka) is a plus.Experience with data security, lineage, and cataloging tools (e.g., Unity Catalog, Collibra).Preferred Qualifications:Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.Microsoft Azure Data Engineer Associate or equivalent certifications preferred.Experience in data governance processes and supporting enterprise analytics platforms.Knowledge of containerization (e.g., Docker) and CI/CD pipelines in DevOps environments.