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Weekend Amazon Data Engineer Jobs in Missouri (NOW HIRING)

Data Engineer Lead

Kansas City, MO · On-site

$111K - $134K/yr

Amazon S3, AWS Glue, Amazon Athena, AWS Lambda, Amazon Redshift, Amazon EMR. • Design secure ... data engineering team. • Lead sprint planning, backlog grooming, estimation, and delivery ...

New

Sr Data Engineer

Lake Saint Louis, MO · On-site

$108K - $130K/yr

Senior Data Engineer Position Purpose: This position will provide the IT Shared Services with a ... CockroachDB, Amazon Aurora and Redis; Linux - RedHat; Continuous Integration and Deployment ...

Databricks Data Engineer

Kansas City, MO · On-site

$111K - $134K/yr

Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) * Ability to travel 50 ... As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based ...

Data Engineer - Manager

Saint Louis, MO · On-site

$99K - $232K/yr

... Amazon Web Services (AWS) and Azure Data Factory to enhance data engineering capabilities - Leading teams in the strategic planning and execution of data-driven projects - Overseeing the deployment ...

Data Engineer - Manager

Kansas City, MO · On-site

$99K - $232K/yr

... Amazon Web Services (AWS) and Azure Data Factory to enhance data engineering capabilities - Leading teams in the strategic planning and execution of data-driven projects - Overseeing the deployment ...

$109K - $130K/yr

Data Engineer The candidate must be committed to move to St. Louis and live here 100% from day 1. ... weekend hours as needed

... as S3, Amazon RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud ... DevOps pipelines - Implementing data security practices using AWS, Azure, GCP, Snowflake or ...

... as S3, Amazon RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud ... DevOps pipelines - Implementing data security practices using AWS, Azure, GCP, Snowflake or ...

Sr Databricks Data Engineer

Kansas City, MO

$111K - $134K/yr

Bachelor's degree in Computer Science, Engineering, or a related field 5+ years of hands-on experience in data engineering with a focus on Databricks on Amazon Web Services (AWS), Microsoft Azure, or ...

$81K - $111K/yr

Senior Data Engineer FUGA is a subsidiary of Downtown Music Holdings and provides forward-thinking ... and Amazon Music while helping them get the most from their music, whether that's with award ...

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Showing results 1-20

Weekend Amazon Data Engineer information

What are Weekend Amazon Data Engineers?

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 an 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 are the most commonly searched types of Amazon Data Engineer jobs in Missouri? The most popular types of Amazon Data Engineer jobs in Missouri are:
What are popular job titles related to Weekend Amazon Data Engineer jobs in Missouri? For Weekend Amazon Data Engineer jobs in Missouri, the most frequently searched job titles are:
What cities in Missouri are hiring for Weekend Amazon Data Engineer jobs? Cities in Missouri with the most Weekend Amazon Data Engineer job openings:

Data Engineer Lead

Scalence L.L.C.

Kansas City, MO • On-site

$111K - $134K/yr

Full-time

Posted 9 hours ago


Job description

Job Summary:
Scalence L.L.C. is seeking a highly experienced Lead Data Engineer to design, develop, and support enterprise-scale data platforms on AWS. The role involves technical leadership, hands-on development, and stakeholder management while building scalable cloud data solutions.
Responsibilities:
• Design, develop, and maintain scalable data pipelines using AWS cloud services.
• Build robust ETL/ELT workflows using Python, PySpark, AWS Glue, and SQL.
• Develop solutions for processing structured, semi-structured, and large-scale datasets.
• Implement enterprise Data Lake/Lakehouse solutions using Amazon S3.
• Build reusable data ingestion and transformation frameworks.
• Develop and optimize solutions using: Amazon S3, AWS Glue, Amazon Athena, AWS Lambda, Amazon Redshift, Amazon EMR.
• Design secure, scalable, and cost-efficient cloud data architectures.
• Optimize storage, partitioning, compression, and query performance.
• Work with Parquet, ORC, and Avro file formats.
• Design high-performance batch data pipelines.
• Optimize Spark jobs and SQL queries for large datasets.
• Improve pipeline reliability, scalability, and operational efficiency.
• Implement monitoring, logging, and alerting for data workflows.
• Serve as the technical lead and Agile anchor for the data engineering team.
• Lead sprint planning, backlog grooming, estimation, and delivery tracking.
• Collaborate with Product Owners, Scrum Masters, Architects, and business stakeholders.
• Mentor junior engineers and establish engineering best practices.
• Conduct code reviews, design reviews, and technical walkthroughs.
• Provide L2/L3 production support for enterprise data platforms.
• Troubleshoot pipeline failures and performance issues.
• Perform Root Cause Analysis (RCA) and implement preventive solutions.
• Participate in incident management and on-call support.
• Utilize CloudWatch and monitoring tools to ensure platform health.
• Implement data quality validation and reconciliation processes.
• Ensure data integrity, lineage, governance, and compliance.
• Develop monitoring frameworks for data quality and operational metrics.
• Implement CI/CD pipelines for data engineering solutions.
• Use Git, Jenkins, AWS CodePipeline, or similar deployment tools.
• Support Infrastructure as Code using Terraform or CloudFormation.
• Automate deployment, testing, and operational processes.
Qualifications:
Required:
• 8–10+ years of experience in designing, developing, and supporting enterprise-scale data platforms on AWS
• Strong expertise in AWS Data Services
• Strong expertise in Python
• Strong expertise in PySpark
• Strong expertise in SQL
• Strong expertise in ETL/ELT development
• Strong expertise in Data Lake/Lakehouse architectures
• Technical leadership experience
• Hands-on development experience
• Agile delivery ownership experience
• Production support experience
• Stakeholder management experience
• Experience in building scalable, secure, and high-performance cloud data solutions
• Experience in designing, developing, and maintaining scalable data pipelines using AWS cloud services
• Experience in building robust ETL/ELT workflows using Python, PySpark, AWS Glue, and SQL
• Experience in developing solutions for processing structured, semi-structured, and large-scale datasets
• Experience in implementing enterprise Data Lake/Lakehouse solutions using Amazon S3
• Experience in building reusable data ingestion and transformation frameworks
• Experience in developing and optimizing solutions using Amazon S3, AWS Glue, Amazon Athena, AWS Lambda, Amazon Redshift, and Amazon EMR
• Experience in designing secure, scalable, and cost-efficient cloud data architectures
• Experience in optimizing storage, partitioning, compression, and query performance
• Experience in working with Parquet, ORC, and Avro file formats
• Experience in designing high-performance batch data pipelines
• Experience in optimizing Spark jobs and SQL queries for large datasets
• Experience in improving pipeline reliability, scalability, and operational efficiency
• Experience in implementing monitoring, logging, and alerting for data workflows
• Experience in serving as the technical lead and Agile anchor for the data engineering team
• Experience in leading sprint planning, backlog grooming, estimation, and delivery tracking
• Experience in collaborating with Product Owners, Scrum Masters, Architects, and business stakeholders
• Experience in mentoring junior engineers and establishing engineering best practices
• Experience in conducting code reviews, design reviews, and technical walkthroughs
• Experience in providing L2/L3 production support for enterprise data platforms
• Experience in troubleshooting pipeline failures and performance issues
• Experience in performing Root Cause Analysis (RCA) and implementing preventive solutions
• Experience in participating in incident management and on-call support
• Experience in utilizing CloudWatch and monitoring tools to ensure platform health
• Experience in implementing data quality validation and reconciliation processes
• Experience in ensuring data integrity, lineage, governance, and compliance
• Experience in developing monitoring frameworks for data quality and operational metrics
• Experience in implementing CI/CD pipelines for data engineering solutions
• Experience in using Git, Jenkins, AWS CodePipeline, or similar deployment tools
• Experience in supporting Infrastructure as Code using Terraform or CloudFormation
• Experience in automating deployment, testing, and operational processes
Company:
In today’s dynamic and competitive market, success hinges on mastering three key areas: Data Intelligence, Business Resilience, and Digital Experience. Founded in , the company is headquartered in Morristown, New Jersey, US, , with a team of 501-1000 employees. The company is currently Late Stage.