ZipRecruiter

Log In

2

Entry Level Databricks Data Engineer Jobs in Charlotte, NC

Ryan Consulting Group

Be Seen First

Data Engineer ETL

Charlotte, NC · On-site

$75K - $125K/yr

No C2C or third parties Fulltime W2 Prefer Charlotte NC Data Engineer Company is looking for an ... Certifications in SnowFlake, AWS or others preferred (Databricks and dbt)

VHB

Entry Level Data Architect

Charlotte, NC · Hybrid

$95K - $98K/yr

Overview ABOUT THE POSITION VHB is seeking a talented entry-level Data Architect to join our data ... Working knowledge of Python and C# programming * Familiarity with ETL/ELT pipelines using Azure ...

VHB

Entry Level Data Architect

Charlotte, NC · Hybrid

$95K - $98K/yr

Overview ABOUT THE POSITION VHB is seeking a talented entry-level Data Architect to join our data ... Working knowledge of Python and C# programming * Familiarity with ETL/ELT pipelines using Azure ...

SEI

Data and Analytics Consultant

Charlotte, NC

Must have experience in architecting and implementing data architecture, data engineering ... Databricks or similar technologies. Advanced Analytics and Data Visualizations * Extensive ...

Veterans Sourcing Group, LLC

.Net Developer

Charlotte, NC · On-site

$47.25 - $62.25/hr

Net Developer to design and maintain scalable software solutions. The role involves collaborating ... data pipelines using Databricks and SQL Server • Create APIs and backend services using .NET ...

previous pagenext page

Showing results 21-40

All JobsDatabricks Data Engineer JobsEntry Level Databricks Data Engineer JobsEntry Level Databricks Data Engineer Jobs in Charlotte, NC

Entry Level Databricks Data Engineer information

See Charlotte, NC salary details

$29.3K

$67.7K

$115.3K

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

As of Aug 15, 2026, the average yearly pay for entry level databricks data engineer in Charlotte, NC is $67,747.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,300.00 and $76,700.00 per year, depending on experience, location, and employer.

What is an entry level Databricks data engineer?

An Entry Level Databricks Data Engineer is a professional who uses Databricks, a cloud-based data analytics platform, to design, build, and maintain data pipelines. They are responsible for preparing and processing large datasets, ensuring data quality, and enabling analytics and machine learning workflows. Typically, they work with tools such as Apache Spark, SQL, and Python, and collaborate with data analysts and data scientists to deliver data-driven solutions. As entry-level engineers, they are expected to have foundational knowledge of data engineering concepts and be eager to learn more advanced techniques on the job.

What are the key skills and qualifications needed to thrive as an entry level Databricks data engineer?

To thrive as an Entry Level Databricks Data Engineer, you need a foundational understanding of data engineering concepts, SQL, and Python or Scala, typically supported by a relevant degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (like AWS or Azure), and optional certifications such as Databricks Data Engineer Associate are highly valuable. Strong analytical thinking, attention to detail, and effective communication skills help you collaborate with teams and solve complex data challenges. These skills and qualities are essential for building reliable data pipelines, ensuring data quality, and delivering actionable insights in a fast-paced environment.

What are some common challenges faced by entry level Databricks data engineers, and how can they effectively overcome them?

Entry-level Databricks Data Engineers often face challenges such as learning to optimize Apache Spark jobs, managing complex data pipelines, and understanding cloud-based workflows. To overcome these, it's important to dedicate time to hands-on practice with Databricks notebooks, collaborate closely with more experienced engineers, and actively participate in code reviews and team discussions. Leveraging Databricks' extensive documentation and community forums can also help troubleshoot issues and stay updated on best practices.

What are the most commonly searched types of Databricks Data Engineer jobs in Charlotte, NC?

The most popular types of Databricks Data Engineer jobs in Charlotte, NC are:

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

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

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

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

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

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

Entry Level Databricks Data Engineer jobs near you
Infographic showing various Entry Level Databricks Data Engineer job openings in Charlotte, NC as of June 2026, with employment types broken down into 100% Full Time. Highlights an 33% In-person, 33% Hybrid, and 34% Remote job distribution, with an average salary of $67,747 per year, or $32.6 per hour.

Data Engineer ETL

Ryan Consulting Group

Charlotte, NC • On-site

$75K - $125K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 17 days ago

Be Seen First

After you apply to this job, you can share why you’re interested to jump to the top of the candidate list.

Job description

No C2C or third parties

Fulltime W2

Prefer Charlotte NC


Data Engineer

Company is looking for an experienced Mid-Level Data Engineer to design, build, and operate scalable data pipelines and data platforms supporting banking and financial services data domains, including customer, account, transaction, and product data.


This role operates within a regulated financial services environment and partners closely with data architecture, analytics, risk, and technology teams to deliver secure, reliable, and analytics ready data products using Snowflake and AWS.

MAIN DUTIES & RESPONSIBILITIES:

• Design, develop, and maintain ELT/ETL pipelines for batch and event driven data ingestion using Snowflake and AWS.

• Engineer and optimize Snowflake data models (tables, views, secure data shares) to support analytics, reporting, and downstream consumption.

• Develop scalable data processing solutions using SQL and Python.

• Integrate with AWS services such as S3, Lambda, Glue, and IAM to support data ingestion, processing, and access management.

• Build and maintain pipelines handling financial transactions and customer data, ensuring accuracy, completeness, and auditability.

• Apply data quality checks, reconciliation logic, and monitoring appropriate for regulated financial data.

• Partner with data architects to align pipelines with enterprise data models, standards, and governance expectations.

• Support production deployments using Git based version control, CI/CD pipelines, and infrastructure as code practices.

• Collaborate in Agile delivery teams, contributing to sprint planning, design reviews, and technical documentation.

• Other duties may be assigned.

MINIMUM REQUIREMENTS:

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field required.

• Three (3)+ years of professional experience in Data Engineering or a related role required.

• Minimum education and experience required can be substituted with the equivalent combination of education, training and experience that provides the required knowledge skills and abilities.

• Strong hands on experience with Snowflake, including data ingestion, transformations, and performance optimization.

• Experience working within AWS cloud environments, particularly with S3 and serverless services.

• Advanced SQL skills and experience working with large, complex datasets.

• Proficiency in Python for data processing and pipeline automation.

• Experience with modern data engineering tools and frameworks (e.g., dbt, Airflow, Spark/PySpark, or equivalent).

• Familiarity with Git, CI/CD practices, and production support workflows.

PREFERRED QUALIFICATIONS:

• Experience working in banking, financial services, fintech, or other regulated industries, as well as financial data domains and data governance concepts.

• Experience supporting analytics or BI tools (e.g., Tableau, Looker, Amazon QuickSight).

• Exposure to streaming or near real time data (Kafka, Kinesis, or event driven architectures).

• Certifications in SnowFlake, AWS or others preferred (Databricks and dbt).