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Associate Data Engineering Jobs in Charlottesville, VA

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Associate Data Engineering information

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$14

$32

$55

How much do associate data engineering jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for associate data engineering in Charlottesville, VA is $32.81, according to ZipRecruiter salary data. Most workers in this role earn between $24.33 and $38.89 per hour, depending on experience, location, and employer.

What are some typical projects an Associate Data Engineer might work on in their first year?

In their first year, an Associate Data Engineer often works on building and maintaining data pipelines, cleaning and transforming raw data, and supporting the integration of new data sources. They may also assist in optimizing existing data workflows for better performance and reliability, as well as collaborating closely with data analysts and senior engineers to ensure data quality and accessibility. These projects help new team members develop a strong understanding of the organization's data infrastructure and best practices in data engineering.

What does an associate data engineer do?

An associate data engineer supports data collection, processing, and storage by developing and maintaining data pipelines and workflows. They often work with tools like SQL, Python, and cloud platforms, and may assist in data quality and integration tasks under the supervision of senior engineers.

What are the key skills and qualifications needed to thrive as an Associate Data Engineer, and why are they important?

To thrive as an Associate Data Engineer, a solid understanding of database systems, SQL, data modeling, and a relevant bachelor's degree in computer science or a related field is essential. Familiarity with ETL tools, cloud platforms like AWS or Azure, and programming languages such as Python or Java is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help set candidates apart in collaborative, data-driven environments. These skills and qualities are crucial for building reliable data pipelines, ensuring data quality, and enabling actionable business insights.

What is an Associate Data Engineer?

An Associate Data Engineer is an entry-level professional who assists in designing, building, and maintaining data pipelines and infrastructure. They typically work with senior data engineers to ensure data is collected, stored, and processed efficiently for analytics and business use. Responsibilities often include data cleaning, integration, and supporting the development of scalable data solutions. Associate Data Engineers usually have foundational knowledge of programming, databases, and cloud technologies.

What engineers make $500,000?

Senior data engineers, especially those with extensive experience, advanced skills in cloud platforms, and expertise in big data tools, can earn $500,000 or more annually. High compensation often involves leadership roles, specialized knowledge, or working in high-demand industries such as finance or technology. Achieving this level typically requires a combination of technical proficiency, certifications, and strategic career development.

What is the difference between Associate Data Engineering vs Data Engineer?

AspectAssociate Data EngineeringData Engineer
Required CredentialsBachelor's degree in CS, IT, or related field; some certificationsBachelor's or master's degree; extensive experience preferred
Work EnvironmentEntry-level, team-focused, supporting data pipelinesDesigning, building, and maintaining large-scale data systems
Employer & Industry UsageCommon in tech companies, finance, healthcareUsed across industries for advanced data infrastructure roles
Search & Comparison IntentEntry-level, learning, support rolesAdvanced, specialized data infrastructure roles

The main difference between Associate Data Engineering and Data Engineer lies in experience and responsibilities. Associate Data Engineers are typically entry-level, focusing on supporting data pipelines and gaining hands-on experience. Data Engineers have more experience, handling complex data architecture, optimization, and system design. Both roles require similar educational backgrounds, but Data Engineers usually have more technical expertise and responsibility.

Can I make 200K as a data engineer?

Senior data engineers with extensive experience, specialized skills in tools like Spark or cloud platforms, and working in high-cost-of-living areas can earn salaries around or above $200,000 annually. Entry-level or mid-level data engineers typically earn less, with salaries increasing with expertise, certifications, and industry demand.

What engineers make 200,000 a year?

Senior data engineers and specialized software engineers often earn $200,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and certifications. High salaries are common in competitive markets and large organizations that require complex data infrastructure and engineering expertise.
What are the most commonly searched types of Data Engineering jobs in Charlottesville, VA? The most popular types of Data Engineering jobs in Charlottesville, VA are:
What cities near Charlottesville, VA are hiring for Associate Data Engineering jobs? Cities near Charlottesville, VA with the most Associate Data Engineering job openings:
Associate Data Engineering jobs near you

Associate Bioinformatics Data Scientist

Signature Science, LLC

Charlottesville, VA

$75K/yr

Full-time

Posted 29 days ago

Job description

Position Purpose:   

A bioinformatics data scientist is responsible for providing experimental design consulting and data analysis for large, high-throughput genomic experiments, with a focus on forensics and metagenomics. The bioinformatics data scientist will be responsible for designing and implementing annotated code for managing, manipulating, and analyzing large-scale genomic data, and for preparing thorough documentation and reporting.

This position is a full-time, on-site role at the Signature Science office in Charlottesville, VA.

Essential Duties and Responsibilities:

  • Develop tools for management, analysis and interpretation of high-density microarray and whole genome sequencing data.
  • Manage, manipulate, and analyze data using a combination of R, python, and UNIX tools.
  • Use established domain-specific open-source software and tools to manipulate and analyze genomic data.
  • Implement and execute data processing workflows and automated analytic pipelines.
  • ·     Apply literate‑programming methods to develop reproducible workflows that produce consistent, standardized tables and figures.
  • Conduct workflow benchmarking and documentation, identifying inconsistencies and resolving data problems.
  • Prepare SOPs, document source code/workflows, and write reports to summarize computational requirements, processing status, and customized analysis results.

Required Knowledge, Skills & Abilities:

  • Advanced proficiency working in a Unix/Linux environment.
  • Advanced proficiency with open-source software, tools, and databases for analyzing next-generation sequencing data (whole-genome sequencing, RNA-seq, epigenetics, microbiome, and metagenomics).
  • Proficiency working with and developing using Docker and/or Singularity container technology.
  • Proficiency using version Control software (e.g., Git or similar) to manage programming code.
  • Proficiency with Python, Perl, or another scripting language.
  • Proficiency with R, RMarkdown, and the "tidyverse" tools for data analysis.
  • Preferred: Experience with NextFlow, SnakeMake, or similar workflow/pipeline management systems.
  • Preferred: Familiarity with developing and querying relational databases.
  • Preferred: Familiarity with AWS and/or Azure cloud computing.

Education/Experience:

  • BA or BS in Computer Science, Bioinformatics, or related field
  • Experience managing and analyzing large-scale datasets produced sequencing platforms and delivering solutions for managing, visualizing, analyzing, and interpreting genomic data
  • Experience using Linux/Unix text processing tools, R, and other open-source tooling to manipulate and format data, to assess data quality, and analyze data.

Clearance:

  • This position requires that the candidate be willing and able to complete a successful background screening for a security clearance. Candidates with a current security clearance will receive preference.

 

Supervisory Responsibilities:

  • May serve as a bioinformatics task lead.

 

Working Conditions/ Equipment:

  • Ability to work in varying conditions to include: traditional office environments with sedentary extended periods required for code development and testing.