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Weekend Amazon Data Engineer Jobs in Tooele, UT (NOW HIRING)

Data Engineer

Salt Lake City, UT · On-site

$95 - $135/hr

Red Cat Corporate - Salt Lake City, UT 84115 Position Summary We're hiring a Data Engineer to build ... Occasional off‑hours or weekend work required for emergency facility responses or projects as ...

Senior Data Engineer

Salt Lake City, UT · On-site

$102K - $139K/yr

Position Summary: The Senior Data Engineer will design, build, and maintain serverless data ... Kafka, Amazon Kinesis, or comparable technologies; strong understanding of event schemas ...

Senior Data Engineer

South Jordan, UT · On-site

$100K - $137K/yr

Strong DB Expertise in an Amazon environment (RDS, Postgres, and DynamoDB) * Strong ETL Experience ... Familiarity with asynchronous programming Benefits Key competencies at Arturo: * Willingness to ...

Senior Automation Engineer

West Jordan, UT · On-site

$97K - $127K/yr

Operations is at the heart of Amazon's business. We are known for our speed, accuracy, and ... weekends, nights, and/or holidays - 4+ years of process or production environment related PLC ...

... Amazon (blue badge/FTE) experience - Work a flexible schedule/shift/work area, including weekends ... degree in Engineering, Operations, Supply Chain/Logistics, or a related field. - Industry ...

... data-driven decisions and analytical problem-solving. Our Operation's workflow has three major ... Amazon (blue badge/FTE) experience - Work a flexible schedule/shift/work area, including weekends ...

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Weekend Amazon Data Engineer information

See Tooele, UT salary details

$41.8K

$121.8K

$166.6K

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

As of Sep 5, 2026, the average yearly pay for weekend amazon data engineer in Tooele, UT is $121,784.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $129,100.00 per year, depending on experience, location, and employer.

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 Tooele, UT are hiring for Weekend Amazon Data Engineer jobs?

Cities near Tooele, UT with the most Weekend Amazon Data Engineer job openings:

Data Engineer

Teal Drones

Salt Lake City, UT • On-site

$95 - $135/hr

Other

Posted 4 days ago


Job description

Job DetailsJob Location: Red Cat Corporate - Salt Lake City, UT 84115

Position Summary

We’re hiring a Data Engineer to build our data foundation from the ground up.

Today, our data lives across transactional databases, SaaS tools, and external APIs. Over the next few months, you’ll help us stand up our first analytics data warehouse and build the ETL/ELT pipelines that keep it accurate, fresh, and easy to use.

You won’t be doing this alone—you’ll work closely with stakeholders (Product, Ops, Finance, and Analytics) and with engineering teammates to make pragmatic choices and ship value quickly.

Essential Duties and ResponsibilitiesBuilding Pipelines and Ingestion
  • Build and maintain ETL/ELT pipelines that ingest data from multiple sources (e.g., internal DBs, SaaS tools, and third-party APIs), and keep them running reliably.
  • Implement scheduling/orchestration, retries, and alerting so failures are visible and recoverable.
  • Design pipelines using incremental processing patterns for scalability and cost efficiency.
Standing up the Warehouse and Models
  • Help set up our first cloud data warehouse (e.g., Snowflake or BigQuery) and the initial schema/layout.
  • Add data quality checks (tests, constraints, anomaly detection, reconciliation checks) and fix root causes when numbers look wrong.
  • Create lightweight observability: freshness/SLAs, pipeline run monitoring, and basic lineage documentation.
  • Make thoughtful tradeoffs between performance, usability, and maintainability.
Collaboration and Enablement
  • Work with stakeholders to translate questions into durable datasets (not one-off queries).
  • Document sources, models, and assumptions so teammates can self-serve and onboard quickly.
  • Participate in a reasonable support/on-call rotation once the stack is live.
Required Qualifications
  • Bachelor’s degree in computer science, data engineering, information systems, or equivalent technical degree.
  • 3+ years of data engineering experience, specifically in managing a data warehouse.
  • Strong SQL skills (joins, window functions, building reliable transformation logic).
  • Comfortable in Python (or a similar language) for pipeline code, automation, and data tool glue.
  • Understanding of data warehousing basics: tables, partitions (where relevant), incremental loads, and why modeling choices matter.
  • Some hands‑on exposure to ETL/ELT or pipelines in production or in a substantial project/internship (we care about proof you can ship and debug).
  • Solid engineering habits: Git, readable code, and a willingness to write things down.
Additional Desired Qualifications
  • dbt experience (models + tests + docs) or the ability to ramp quickly.
  • Orchestration experience (Airflow, Dagster, Prefect, or similar).
  • Experience with a cloud data warehouse (Snowflake, BigQuery, Redshift).
  • Experience ingesting data from APIs and messy SaaS exports (rate limits, pagination, schema drift, deduping).
  • Familiarity with basic data quality/observability practices (freshness checks, anomaly detection, monitoring/alerting).
Physical Requirements and Working Conditions
  • Must be able to walk, stand, and navigate large indoor and outdoor facilities for extended periods of time.
  • Ability to lift, carry, and move materials and equipment weighing up to 25 lbs on a regular basis.
  • Use of personal protective equipment (PPE) may be required in designated areas or when performing specific tasks, in accordance with safety protocols and company policy.
  • May be required to climb ladders, stoop, kneel, or crouch during inspections, maintenance walk-throughs, or emergency response situations.
  • Regular exposure to facility operations including noise, dust, temperature fluctuations, and industrial equipment.
  • Occasional off‑hours or weekend work required for emergency facility responses or projects as needed
  • Requires frequent use of a computer and other standard office equipment for documentation, communication, and coordination tasks.
Background Check

This position will require successfully completing a post-offer background check. Qualified candidates with a criminal history will be considered and are not automatically disqualified, consistent with federal and state law.

EEO and ITAR/EAR Work Authorization Disclosure

Red Cat Holdings provides equal employment opportunities (EEO) to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This position requires direct or indirect access to hardware, software, technology or technical data controlled under the International Traffic in Arms Regulations (ITAR) and the Export Administration Regulations (EAR). Successful candidates for positions subject to ITAR/EAR restrictions must provide proof of U.S. Citizenship or Permanent Residence and must not require sponsorship for export-restricted work authorization.

E-Verify

The company participates E-Verify ensure eligibility for employment and compliance with Right to Work rules.

Compensation: Base pay, plus generous annual equity package and potential bonuses.

Qualifications
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