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Weekend Amazon Data Engineer Jobs in Oregon (NOW HIRING)

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Weekend Amazon Data Engineer information

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 in Oregon are hiring for Weekend Amazon Data Engineer jobs?

Cities in Oregon with the most Weekend Amazon Data Engineer job openings:

Weekend Amazon Data Engineer jobs near you

Need Sr Big Data Engineer at Beaverton, OR Only W2

Beaverton, OR

USM
See more jobs at USMexternal

$58 - $76.75/hr

Contractor

Re-posted 20 days ago

Job description

Job Description

Hi,

We have immediate opportunity with our direct client send your resume asap upon your interest. Thank you.

Position: Sr Big Data Engineer

Location: Beaverton, OR.

Duration: Long Term

Skills

Typical Office: This is a typical office job, with no special physical requirements or unusual work environment.

Core responsibilities: Expert data engineers will work with product teams across client to help automate and integrate various of data domains with a wide variety of data profiles (different scale, cadence, and volatility) into client's next-gen data and analytics platform. This is an opportunity to work across multiple subject areas and source platforms to ingest, organize, and prepare data through cloud-native processes.

Required skills/experience:

- 5+ years of professional development experience between either Python (preferred) or Scala/Java; familiarity with both is ideal

- 5+ years of data-centric development with a focus on efficient data access and manipulation at multiple scales

- 3+ years of experience with the HDFS ecosystem of tools (any distro, Spark experience prioritized)

- 3+ years of significant experience developing within the broader AWS ecosystem of platforms and services

- 3+ years of experience optimizing data access and analysis in non-HDFS data platforms (Traditional RDMS's, NoSQL / KV stores, etc)

- Direct task development and/or configuration experience with a remote workflow orchestration tool - Airflow (preferred), Amazon Data Pipeline, Luigi, Oozie, etc.

- Intelligence, strong problem-solving ability, and the ability to effectively communicate to partners with a broad spectrum of experiential backgrounds

Several of the following skills are also desired:

- A demonstrably strong understanding of security and credential management between application / platform components

- A demonstrably strong understanding of core considerations when working with data at scale, in both file-based and database contexts, including SQL optimization

- Direct experience with Netflix Genie is another huge plus

- Prior experience with the operational backbone of a CI/CD environment (pipeline orchestration + configuration management) is useful

- Clean coding practices, passion for development, being a generally good team player, etc, etc (and experience with GitHub) is always nice

Keys to Success:

- Deliver exceptional customer service

- Demonstrate accountability and integrity

- Be willing to learn and adapt every day

- Embrace changeSkills

Regards
Nithya

Additional Information

All your information will be kept confidential according to EEO guidelines. please send the profiles to nithyar(at)usmsystems.com and contact No# 703-794-2380.

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