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Weekend Data Engineering Jobs in Richmond, VA (NOW HIRING)

CEI

Data Engineer

Richmond, VA · On-site

$100 - $120/hr

Required 5 to 7+ years of Data Engineering experience. * ETL development and process support; may require weekend/off-business-hours work. Key Responsibilities * Build end-to-end data pipelines and ...

NimbusAITech LLC

Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

Python -- hands-on experience required SQL -- strong hands-on experience required AWS -- required, hands-on cloud data engineering experience PySpark -- hands-on experience building and optimizing ...

RIT Solutions, Inc.

Data Engineer (763232)

Richmond, VA · On-site

$112K - $134K/yr

Responsibilities : • Strong Data engineering fundamentals. • Utilize Big data frameworks like Spark/Databricks. • Training LLMs with structed and unstructured data sets. • Understanding of ...

3B Staffing LLC

Agentic Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

Design and build the data architecture, including databases, data lakes to support various data engineering tasks. * Develop and manage Extract, Load, transform (ELT) processes to ensure data is ...

3B Staffing LLC

Agentic Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

Design and build the data architecture, including databases, data lakes to support various data engineering tasks. * Develop and manage Extract, Load, transform (ELT) processes to ensure data is ...

Deloitte

Data Engineer II

Richmond, VA · On-site

$113K - $136K/yr

The ideal candidate brings technical experience in data engineering, strong problem-solving skills, and the ability to work across teams in a dynamic environment. Work you'll do As a Data Engineer II ...

Deloitte

Data Engineer II

Richmond, VA · On-site

$113K - $136K/yr

The ideal candidate brings technical experience in data engineering, strong problem-solving skills, and the ability to work across teams in a dynamic environment. Work you'll do As a Data Engineer II ...

Snowrelic Inc

Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

Apply best practices in cloud data engineering, including security and compliance standards. Required Skills: * Scripting: Proficiency in Python , Bash , or Shell scripting . * Cloud Technologies:

Deloitte

Palantir Foundry Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

The ideal candidate brings technical experience in data engineering, strong problem-solving skills, and the ability to work across teams in a dynamic environment. Work you'll do As a Data Engineer II ...

Pwc

Data Engineer - Senior Manager

Richmond, VA · On-site

$124K - $280K/yr

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

IT America Inc

AWS Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

Bachelor's degree in Computer Science, Engineering, or related field. * Demonstrated expertise in developing data pipelines with Python and PySpark, with a strong emphasis on utilizing AWS Glue, EMR ...

Apex Systems

Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

Data engineering certification (e.g., IBM Certified Data Engineer). * 3+ years working with data migrations and/or implementations. Everforth Apex is a world-class IT services company that serves ...

Bitwise

Data Engineer Lead

Richmond, VA · On-site

$113K - $136K/yr

... Data Engineering teams working on ADF & Databricks. Work with the teams providing technical approaches and solutions. • Proven experience with data warehousing concepts and best practices. • ...

Zortech Solutions

Agentic Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

Design and build data architecture, including databases, data lakes to support various data engineering tasks. * Develop and manage Extract, Load, transform (ELT) processes to ensure data is ...

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All JobsData Engineering JobsWeekend Data Engineering JobsWeekend Data Engineering Jobs in Richmond, VA

Weekend Data Engineering information

See Richmond, VA salary details

$44K

$128.4K

$175.7K

How much do weekend data engineering jobs pay per year?

As of Sep 5, 2026, the average yearly pay for weekend data engineering in Richmond, VA is $128,371.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,300.00 and $136,100.00 per year, depending on experience, location, and employer.

What is the difference between Weekend Data Engineering vs Weekend Data Analysis?

AspectWeekend Data EngineeringWeekend Data Analysis
Required SkillsData pipeline development, SQL, Python, cloud platformsData interpretation, visualization, SQL, Excel
Work EnvironmentTechnical teams, data infrastructure projectsBusiness teams, reporting and insights
CertificationsData engineering certifications (e.g., Google Cloud, AWS)Data analysis certifications (e.g., Microsoft, Tableau)

Weekend Data Engineering focuses on building and maintaining data pipelines and infrastructure, requiring technical skills and cloud platform knowledge. In contrast, Weekend Data Analysis emphasizes interpreting data, creating reports, and providing insights, often using visualization tools. Both roles are essential in data-driven organizations but serve different functions during weekend projects or part-time work.

Are weekend data engineers still in demand?

Weekend data engineers are still in demand as companies seek flexible staffing for data pipeline maintenance, troubleshooting, and project work outside regular hours. Skills in cloud platforms, SQL, and data tools like Apache Spark remain valuable, and many organizations require support during weekends to ensure continuous data operations.

Do weekend data engineers need to work on weekends?

Weekend data engineers typically work during regular business hours and do not usually need to work on weekends unless there are urgent data issues or scheduled maintenance. Some roles may require occasional weekend work for system updates or troubleshooting, but it is not a standard expectation for all positions. Flexibility depends on the company's policies and project deadlines.

What are the most commonly searched types of Data Engineering jobs in Richmond, VA?

The most popular types of Data Engineering jobs in Richmond, VA are:

Weekend Data Engineering jobs near you

Data Engineer

CEI

Richmond, VA • On-site

$100 - $120/hr

Other

Re-posted 2 days ago

Job description

Richmond , Virginia Contract Hybrid Aug 3, 2026

Role Summary

The Senior Data Engineer is a hands-on expert and technical leader, actively engaged in designing, building, and optimizing scalable, reliable data pipelines at an enterprise level. This role not only guides architectural decisions but also directly implements advanced ELT solutions, troubleshoots complex data challenges, and ensures best practices through practical, high-impact contributions.

This role combines deep hands-on expertise with technical ownership, mentoring, and architectural alignment. The Senior Data Engineer drives and implements data engineering best practices, ensures high standards for quality and security, and partners with architecture and platform teams to improve the overall data ecosystem.

Required Skills & Experience
  • Advanced expertise in SQL, ELT patterns, and performance tuning.
  • Strong experience with Oracle Exadata, Snowflake or similar cloud/on-prem data warehouses.
  • Hands-on experience with enterprise ETL/ELT platforms (e.g., Talend, dbt, Informatica).
  • Deep understanding of data warehousing architecture and dimensional modeling.
  • Experience designing and supporting large-scale, production data pipelines.
  • Strong scripting experience (Python, shell).
  • Experience with data virtualization tools (e.g., Denodo, Composite, Dremio, Starburst).
  • Experience with DataOps practices, CI/CD, and observability.
  • Required 5 to 7+ years of Data Engineering experience.
  • ETL development and process support; may require weekend/off-business-hours work.
Key Responsibilities
  • Build end-to-end data pipelines and ETL/ELT solutions to support analytics, reporting, and AI/ML use cases.
  • Apply scalable patterns for batch and incremental processing by developing, testing, and deploying data workflows.
  • Review and implement data modeling, transformation logic, and performance strategies.
  • Evaluate, select, and integrate tooling, frameworks, and platform capabilities.
  • Build complex, high-volume data pipelines using SQL-centric ETL/ELT patterns.
  • Design and implement scalable streaming pipelines to process real-time data.
  • Lead performance tuning efforts across pipelines, warehouses, and workloads.
  • Ensure data pipelines are resilient, observable, and production ready.
  • Implement enterprise-grade error handling, restartability, and monitoring.
  • Build and maintain scalable, low-latency streaming data pipelines using Kafka, Kinesis, or Spark Streaming.
  • Perform on-the-fly data cleaning, validation, and enrichment.
  • Utilize indexing and partitioning strategies to optimize warehouse and big data environments.
  • Implement standards for data quality checks, validation, and reconciliation.
  • Ensure pipelines meet security, access control, and governance requirements.
  • Partner with governance and DataOps teams on metadata, lineage, and auditability.
  • Improve operational monitoring, alerting, and incident response processes.
  • Identify reliability, performance, and cost optimization opportunities.
  • Support production troubleshooting and root cause analysis.
  • Investigate data quality incidents and identify design/coding gaps.
  • Participate in design and code reviews.
  • Partner with infrastructure teams, application teams, and architects on complex transformations.
  • Translate ambiguous requirements into technical solutions.
  • Work across complex multi-platform environments.
  • Delivering at Pace
  • Effective Communication
  • Ownership and Adaptability
  • Ability to Work Independently
  • Achievement Orientation
  • Concern for Quality
  • Flexibility
Preferred Qualifications
  • Experience supporting AI/ML or advanced analytics pipelines.
  • Cloud platform experience (AWS, Azure, or GCP).
  • Prior experience influencing enterprise data standards or reference architecture.
  • Experience optimizing cost and performance in cloud data warehouses.
  • Hands-on experience with Cribl, Apache Kafka, Kafka Connect, Spark Streaming, or Apache Flink.
Education
  • Bachelor's Degree or higher required
  • Computer Science, Information Systems, Mathematics, or related discipline
Preferred Industry Background
  • High preference for candidates with large-scale utility industry experience.
  • Will also consider candidates supporting large-scale capital projects.
Data Engineer

Richmond, VA 23219 (hybrid)
Pay: $100,000-120,000

Role Summary

The Senior Data Engineer is a hands-on expert and technical leader, actively engaged in designing, building, and optimizing scalable, reliable data pipelines at an enterprise level. This role not only guides architectural decisions but also directly implements advanced ELT solutions, troubleshoots complex data challenges, and ensures best practices through practical, high-impact contributions.

This role combines deep hands-on expertise with technical ownership, mentoring, and architectural alignment. The Senior Data Engineer drives and implements data engineering best practices, ensures high standards for quality and security, and partners with architecture and platform teams to improve the overall data ecosystem.

Required Skills & Experience
  • Advanced expertise in SQL, ELT patterns, and performance tuning.
  • Strong experience with Oracle Exadata, Snowflake or similar cloud/on-prem data warehouses.
  • Hands-on experience with enterprise ETL/ELT platforms (e.g., Talend, dbt, Informatica).
  • Deep understanding of data warehousing architecture and dimensional modeling.
  • Experience designing and supporting large-scale, production data pipelines.
  • Strong scripting experience (Python, shell).
  • Experience with data virtualization tools (e.g., Denodo, Composite, Dremio, Starburst).
  • Experience with DataOps practices, CI/CD, and observability.
  • Required 5 to 7+ years of Data Engineering experience.
  • ETL development and process support; may require weekend/off-business-hours work.
Key Responsibilities
  • Build end-to-end data pipelines and ETL/ELT solutions to support analytics, reporting, and AI/ML use cases.
  • Apply scalable patterns for batch and incremental processing by developing, testing, and deploying data workflows.
  • Review and implement data modeling, transformation logic, and performance strategies.
  • Evaluate, select, and integrate tooling, frameworks, and platform capabilities.
  • Build complex, high-volume data pipelines using SQL-centric ETL/ELT patterns.
  • Design and implement scalable streaming pipelines to process real-time data.
  • Lead performance tuning efforts across pipelines, warehouses, and workloads.
  • Ensure data pipelines are resilient, observable, and production ready.
  • Implement enterprise-grade error handling, restartability, and monitoring.
  • Build and maintain scalable, low-latency streaming data pipelines using Kafka, Kinesis, or Spark Streaming.
  • Perform on-the-fly data cleaning, validation, and enrichment.
  • Utilize indexing and partitioning strategies to optimize warehouse and big data environments.
  • Implement standards for data quality checks, validation, and reconciliation.
  • Ensure pipelines meet security, access control, and governance requirements.
  • Partner with governance and DataOps teams on metadata, lineage, and auditability.
  • Improve operational monitoring, alerting, and incident response processes.
  • Identify reliability, performance, and cost optimization opportunities.
  • Support production troubleshooting and root cause analysis.
  • Investigate data quality incidents and identify design/coding gaps.
  • Participate in design and code reviews.
  • Partner with infrastructure teams, application teams, and architects on complex transformations.
  • Translate ambiguous requirements into technical solutions.
  • Work across complex multi-platform environments.
Behavioral Expectations
  • Delivering at Pace
  • Collaborative Teamwork
  • Effective Communication
  • Ownership and Adaptability
  • Ability to Work Independently
  • Achievement Orientation
  • Self-Starter
  • Concern for Quality
  • Flexibility
Preferred Qualifications
  • Experience supporting AI/ML or advanced analytics pipelines.
  • Cloud platform experience (AWS, Azure, or GCP).
  • Prior experience influencing enterprise data standards or reference architecture.
  • Experience optimizing cost and performance in cloud data warehouses.
  • Hands-on experience with Cribl, Apache Kafka, Kafka Connect, Spark Streaming, or Apache Flink.
Education
  • Bachelor's Degree or higher required
  • Computer Science, Information Systems, Mathematics, or related discipline
Preferred Industry Background
  • High preference for candidates with large-scale utility industry experience.
  • Will also consider candidates supporting large-scale capital projects.
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