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Weekend Amazon Data Engineer Jobs in Lithonia, GA

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Weekend Amazon Data Engineer information

See Lithonia, GA salary details

$40.6K

$118.4K

$162.1K

How much do weekend amazon data engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for weekend amazon data engineer in Lithonia, GA is $118,426.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $125,500.00 per year, depending on experience, location, and employer.

How much do Weekend Amazon Data Engineers make?

Weekend Amazon Data Engineers typically earn between $50,000 and $100,000 annually, depending on experience, location, and skill set. Compensation may include benefits such as flexible schedules, cloud tools, and data processing platforms like AWS and Spark.

What is a Weekend Amazon Data Engineer?

Weekend Amazon Data Engineers are professionals who work with Amazon's data infrastructure, usually on a part-time or flexible basis during weekends. They are responsible for building, maintaining, and optimizing data pipelines and systems that support data analysis and business decision-making. Their work often involves using Amazon Web Services (AWS) tools, programming languages such as Python or SQL, and collaborating with data scientists or analysts. Weekend roles are ideal for those seeking supplementary income, work-life balance, or an opportunity to gain experience in cloud-based data engineering.

What does a typical weekend look like for a Weekend Amazon Data Engineer, and how does the work schedule differ from weekday roles?

As a Weekend Amazon Data Engineer, you can expect to focus on monitoring data pipelines, addressing urgent data-related issues, and supporting critical deployments that often occur during lower-traffic periods on weekends. This role may involve collaborating with on-call engineers, data analysts, and product teams to ensure data infrastructure stability and resolve incidents quickly. The weekend schedule typically allows for more independent work, but you will still participate in virtual stand-ups or handoff meetings with weekday teams to maintain continuity. Flexibility and strong communication are important, as you'll often be the primary point of contact for data engineering concerns during your shift.

What are the key skills and qualifications needed to thrive as a Weekend Amazon Data Engineer, and why are they important?

To thrive as a Weekend Amazon Data Engineer, you need strong proficiency in data modeling, SQL, and programming languages such as Python or Java, often backed by a degree in computer science or a related field. Familiarity with AWS services (like Redshift, S3, and Glue), ETL tools, and data warehousing certifications is highly valuable. Excellent problem-solving skills, attention to detail, and effective collaboration are standout soft skills for this role. These competencies ensure the reliable and efficient processing of large datasets, supporting business needs even during off-peak times.

What is the difference between Weekend Amazon Data Engineer vs Weekend Amazon Data Analyst?

AspectWeekend Amazon Data EngineerWeekend Amazon Data Analyst
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentData pipelines, cloud platforms, ETL processesData interpretation, reporting, visualization tools
Employer & Industry UsageAmazon, e-commerce, cloud servicesAmazon, retail, marketing teams

Weekend Amazon Data Engineers focus on building and maintaining data infrastructure, while Data Analysts interpret data and generate reports. Both roles often work in the same environment but serve different functions within Amazon's data ecosystem.

What cities near Lithonia, GA are hiring for Weekend Amazon Data Engineer jobs? Cities near Lithonia, GA with the most Weekend Amazon Data Engineer job openings:
Weekend Amazon Data Engineer jobs near you

Cloud Engineer- Data/AI Focused

Innovative Solutions

Atlanta, GA • On-site

$100K - $160K/yr

Full-time

Re-posted 7 days ago

Job description

As a Data & AI Engineer, you'll build and deploy modern data pipelines and generative AI solutions on AWS - from scalable ETL/ELT workflows and cloud data platforms to production-grade RAG systems and AI agents. One engagement you may be designing and optimizing data pipelines using Glue, Lambda, and Redshift, the next you're building GenAI applications powered by Bedrock, Claude, and vector databases to enable intelligent search and automation. You'll work directly with clients to deliver end-to-end data and AI solutions that are secure, scalable, and production-ready.

What You'll Do:

  • Implementing data pipelines using AWS services such as Glue, Lambda, Step Functions, and EMR
  • Creating and maintaining data extraction, transformation, and loading processes
  • Configuring and optimizing AWS database services including RDS, Aurora, Redshift, and DynamoDB
  • Implementing data lakes using S3 and related AWS services
  • Designing and building production-ready Generative AI applications using Amazon Bedrock and foundation models such as Anthropic Claude
  • Building and optimizing RAG (Retrieval-Augmented Generation) pipelines with vector databases
  • Developing AI agents and multi-agent orchestration systems using frameworks like LangChain or LlamaIndex
  • Writing and testing SQL queries and stored procedures
  • Documenting technical solutions and providing knowledge transfer to customers
  • Supporting the implementation of data governance and security controls
  • Troubleshooting and resolving issues with data pipelines and AI services
  • Participating in code reviews and implementing feedback
  • Assisting with proof-of-concept implementations for customer engagements

Required Skills:

  • 5+ years of software engineering experience with at least 2+ years focused on AI/ML, data engineering, or cloud-native development
  • 2+ years of hands-on AWS experience with production deployments
  • 1+ years of direct Generative AI experience (LLMs, embeddings, RAG, agents)
  • Proven track record delivering production AI applications from concept to deployment
  • Strong understanding of software engineering best practices (version control, testing, code review, documentation)
  • Experience working in agile/scrum environments with distributed teams
  • Excellent problem-solving skills and ability to work independently with minimal supervision
  • Strong written and verbal communication skills for client-facing interactions

Preferred:

  • Technical familiarity with AWS data and AI/ML services and modern data engineering practices
  • Hands-on experience with ETL/ELT processes and data transformation
  • Exposure to Generative AI concepts including LLMs, embeddings, RAG, and agent frameworks
  • Ability to write and optimize SQL queries across various database platforms
  • Knowledge of data modeling concepts and best practices
  • Strong analytical and problem-solving skills
  • Eagerness to learn new technologies and keep up with cloud and AI innovations
  • Excellent communication skills with the ability to explain technical concepts clearly
  • Attention to detail and commitment to solution quality
  • Collaborative mindset with strong teamwork capabilities
  • Experience or interest in automation and infrastructure as code
$100,000 - $160,000 a year
The salary range provided is a general guideline. When extending an offer, Innovative considers factors including, but not limited to, the responsibilities of the specific role, market conditions, geographic location, as well as the candidate's professional experience, key skills, and education/training.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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