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Entry Level Streaming Data Engineer Jobs in Charlotte, NC

Sabio infotech

AWS Data Engineer

Charlotte, NC · On-site

$111K - $134K/yr

Data Engineer- AWS & Streaming Location: Fort Mill SC (OR) Charlotte, NC (OR) New York, NY (2-3 Days Hybrid) Experience level - 12+ Years Key Responsibilities: * Develop and maintain scalable ETL/ELT ...

Euclid Innovations

Data Engineer - GCP

Charlotte, NC · On-site

$111K - $134K/yr

Euclid Innovations is seeking a Data Engineer with expertise in Google Cloud Platform. The role ... batch/streaming) • Experience with cloud platforms - GCP (Google Cloud Platform) • BigQuery ...

Redolent, Inc.

Big data engineer - Python

Charlotte, NC · On-site

$54.50 - $72/hr

Experience with SPARK Structured Streaming, Hadoop/Big Data, and Distributed Systems * Working ... Hands-on programming experience in at least one of the following: Scala, Python, PHP, or Shell ...

Ryan Consulting Group

Data Engineer ETL

Charlotte, NC · On-site

$75K - $125K/yr

Engineer and optimize Snowflake data models (tables, views, secure data shares) to support ... Exposure to streaming or near real time data (Kafka, Kinesis, or event driven architectures)

Slalom Consulting

General Information

Charlotte, NC · On-site

$100K - $115K/yr

Data Engineer Who You'll Work With At Slalom we co-create custom software, data, AI, and cloud ... Streaming data platforms for real-time ingestion, event-driven architectures, and analytics. * Data ...

LPL Financial

API & Data Engineer II

Fort Mill, SC

$40.10 - $66.83/hr

Joining as a Data Engineer II, you will be responsible for building and maintaining the sustainable ... Implement messaging and streaming solutions using Kafka. * Write clean, maintainable, and testable ...

LPL Financial LLC

API & Data Engineer II

Fort Mill, SC · On-site

$60 - $80/hr

Joining as a Data Engineer II, you will be responsible for building and maintaining the sustainable ... Implement messaging and streaming solutions using Kafka. * Write clean, maintainable, and testable ...

LPL Financial LLC

API & Data Engineer II

Charlotte, NC · On-site

$60 - $80/hr

Joining as a Data Engineer II, you will be responsible for building and maintaining the sustainable ... Implement messaging and streaming solutions using Kafka. * Write clean, maintainable, and testable ...

LPL Financial

API & Data Engineer II

Fort Mill, SC · On-site

$40.10 - $66.83/hr

Joining as a Data Engineer II, you will be responsible for building and maintaining the sustainable ... Implement messaging and streaming solutions using Kafka. * Write clean, maintainable, and testable ...

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All JobsStreaming Data Engineer JobsEntry Level Streaming Data Engineer JobsEntry Level Streaming Data Engineer Jobs in Charlotte, NC

Entry Level Streaming Data Engineer information

See Charlotte, NC salary details

$43.5K

$126.7K

$173.4K

How much do entry level streaming data engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for entry level streaming data engineer in Charlotte, NC is $126,696.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,800.00 and $134,300.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Streaming Data Engineer vs Data Analyst?

AspectEntry Level Streaming Data EngineerData Analyst
Required SkillsKnowledge of streaming platforms (e.g., Kafka, Spark), basic programming, data modelingData visualization, SQL, statistical analysis, Excel
CertificationsOptional certifications in data engineering or cloud platformsCertifications in data analysis or business intelligence tools
Work EnvironmentDeveloping real-time data pipelines, working with streaming data systemsInterpreting data, creating reports, supporting decision-making
Industry UsageTech, finance, e-commerce, where real-time data processing is criticalMarketing, finance, healthcare, focusing on data insights

In summary, Entry Level Streaming Data Engineers focus on building and maintaining real-time data pipelines using streaming technologies, while Data Analysts interpret and visualize data to support business decisions. Both roles require different skill sets but are essential in data-driven industries.

Can I get an entry level streaming data engineer job with no experience?

Entry level streaming data engineer roles typically require some knowledge of data processing tools like Apache Kafka or Spark, and familiarity with programming languages such as Python or Java. While prior experience is often preferred, candidates with relevant internships, certifications, or strong foundational skills in data concepts can sometimes qualify for entry-level positions. Demonstrating a willingness to learn and understanding of streaming architectures can improve chances of securing such roles.

What is an entry level streaming data engineer?

An entry level streaming data engineer is a professional responsible for designing, building, and maintaining systems that process real-time data streams. They typically work with tools like Apache Kafka, Spark Streaming, or Flink and require foundational knowledge of programming, data architecture, and cloud platforms. This role often involves collaborating with data scientists and software engineers to ensure efficient data flow and availability.

What are popular job titles related to Entry Level Streaming Data Engineer jobs in Charlotte, NC?

For Entry Level Streaming Data Engineer jobs in Charlotte, NC, the most frequently searched job titles are:

What job categories do people searching Entry Level Streaming Data Engineer jobs in Charlotte, NC look for?

The top searched job categories for Entry Level Streaming Data Engineer jobs in Charlotte, NC are:

What cities near Charlotte, NC are hiring for Entry Level Streaming Data Engineer jobs?

Cities near Charlotte, NC with the most Entry Level Streaming Data Engineer job openings:

Entry Level Streaming Data Engineer jobs near you
Infographic showing various Entry Level Streaming Data Engineer job openings in Charlotte, NC as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $126,696 per year, or $60.9 per hour.

Sr. Data Engineer (Mid-Senior Level) - AWS & Streaming eone Infotech

eOne Infotech

Fort Mill, SC • On-site

$100 - $125/hr

Other

Posted 7 days ago

Job description

We are seeking a Mid–Senior Data Engineer with strong expertise in AWS-based data engineering, real-time streaming technologies, and enterprise-grade data quality frameworks. The ideal candidate will design, build, and optimize scalable batch and streaming data pipelines, implement robust data validation and monitoring processes, and support mission-critical analytics platforms.

Key Responsibilities:
  • Develop and maintain scalable ETL/ELT pipelines using AWS Glue, PySpark, and Python
  • Design and manage real-time streaming solutions using Kafka, KSQL, and Apache Flink
  • Implement and enforce comprehensive data quality frameworks, including validation, profiling, monitoring, and reconciliation
  • Optimize data processing performance, scalability, reliability, and cost in cloud environments
  • Collaborate with cross-functional teams to deliver reliable, production-grade data platforms and ensure data integrity across the pipeline
Required Skills:
  • Strong hands-on experience with Python and PySpark
  • Proven expertise in AWS Glue, Lambda, and other cloud-native data services
  • Solid experience with the Kafka ecosystem (topics, partitions, consumer groups, streaming patterns)
  • Demonstrated experience building and supporting data quality frameworks (validation rules, reconciliation checks, profiling, anomaly detection)
  • Strong understanding of distributed data processing and scalable architecture patterns
Good-to-Have Skills:
  • Experience with Apache Flink for real-time stream processing and stateful computations
  • Knowledge of KSQL or other streaming SQL engines
  • Exposure to CI/CD pipelines, IaC (Terraform/CloudFormation), and DevOps practices
  • Familiarity with data lake/lakehouse architectures and table formats such as Iceberg, Delta, or Hudi
  • Experience working in enterprise or financial data environments
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