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Remote Google Quality Rater Jobs in Michigan (NOW HIRING)

Apex Systems

Simulation Quality Analyst

Warren, MI · Remote

$55 - $62/hr

Remote Employment Type: Contract Pay rate: $55-62/hr Role Overview We are seeking a Senior ... Experience with data analysis using tools like Google Sheets, Excel, or SQL. * Familiarity with ...

SkySync

Quality Assurance Tester

Ann Arbor, MI · Remote

... remote staff in all US time zones. Our workforce excels at data governance and managing our ... We need someone who has experience with digital platforms such as Microsoft SharePoint or Google ...

ChristianSky Agency

Sales Associate (Remote)

Lansing, MI · Remote

$14.25 - $19.25/hr

Recognized by Entrepreneur Magazine for fostering a top company culture and consistently rated ... High-Quality Leads: Focus on closing deals with premium, pre‐qualified leads. Health and Life ...

BetterHelp

Psychiatrist - (Remote)

Detroit, MI · Remote

$125 - $171/hr

Provide empathetic, high-quality care and uphold UpLift's clinical and service standards. * Share ... rate, wage, or salary. These estimates are calculated using assumptions regarding number of ...

Deloitte

Databricks Engineer

Detroit, MI · On-site +1

... remote client service delivery. Recruiting for this role ends on 06/30/2026. Work you'll do As a ... Meticulous attention to detail and quality of work product * Ability to build and sustain ...

Learning Care Group

IT Help Desk Agent

Novi, MI · On-site +1

$23.42 - $26/hr

... remote access support, Microsoft 365 and Google Workspace issues, and network and Wi-Fi ... Meet or exceed defined SLA targets for response time, first-contact resolution rate, and customer ...

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Remote Google Quality Rater information

What are the key skills and qualifications needed to thrive as a Remote Google Quality Rater, and why are they important?

To thrive as a Remote Google Quality Rater, you need strong analytical skills, attention to detail, and a solid understanding of current events and online culture, usually requiring at least a high school diploma or equivalent. Familiarity with web browsers, search engines, and online research tools is essential, and training is typically provided through Google's guidelines and evaluation systems. Excellent time management, communication, and the ability to work independently are standout soft skills in this role. These skills are crucial because they ensure accurate evaluation of search results, which directly impacts the quality and relevance of information delivered to users.

What are some common challenges faced by Remote Google Quality Raters, and how can they be managed effectively?

Remote Google Quality Raters often encounter challenges such as interpreting nuanced guidelines, maintaining focus during repetitive tasks, and managing variable workloads. Staying updated with frequent guideline changes and ensuring consistent quality in evaluations are key aspects of the role. To manage these challenges, it's helpful to set a structured daily schedule, actively participate in training sessions, and engage with online communities for peer support. Building effective time-management habits and regularly reviewing guidelines can greatly enhance accuracy and job satisfaction.

What are Remote Google Quality Raters?

Remote Google Quality Raters are individuals who work from home to evaluate the quality and relevance of search engine results provided by Google. Their main role is to assess how well search results match user queries, helping improve the accuracy and usefulness of Google's algorithms. Raters follow specific guidelines to judge search result quality, and their feedback contributes to continuous improvement of Google's search experience. This is typically a part-time, contract-based job that does not involve direct interaction with Google users.

What is the difference between Remote Google Quality Rater vs Remote Search Engine Evaluator?

AspectRemote Google Quality RaterRemote Search Engine Evaluator
CredentialsMinimal; usually high school diploma or equivalentSimilar; high school diploma often required
Work EnvironmentRemote, flexible hours, home-basedRemote, flexible hours, home-based
Employer & IndustryGoogle, tech/advertising industryVarious search engines, tech industry
Job FocusAssessing Google search quality and relevanceEvaluating search engine results for accuracy and relevance

Both roles involve evaluating search results remotely, with similar credentials and work environments. The main difference lies in the employer and specific focus: Google Quality Raters work specifically for Google, while Search Engine Evaluators may work for various companies. Both positions require attention to detail and familiarity with search engines, making them comparable roles in the industry.

What are popular job titles related to Remote Google Quality Rater jobs in Michigan? For Remote Google Quality Rater jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Google Quality Rater jobs in Michigan look for? The top searched job categories for Remote Google Quality Rater jobs in Michigan are:
What cities in Michigan are hiring for Remote Google Quality Rater jobs? Cities in Michigan with the most Remote Google Quality Rater job openings:
Remote Google Quality Rater jobs near you

Google Cloud Platform Data Engineer

Reliable Software Resources

Detroit, MI • Remote

$104.80K - $125.80K/yr

Other

Posted 2 days ago

Job description

Job Role: Google Cloud Platform Data Engineer

Location: Detroit, MI

Hire-type: Contract

Experience: 3–6 years  |  Detroit, MI (mandatory) — Remote up to 50% travel 

Python

Google Cloud Platform Native

BigQuery

ETL / ELT Pipelines

Data Modeling

SQL

ABOUT THE ROLE

As a Google Cloud Platform Data Engineer at DataFactZ you will design, build, and maintain cloud-native data pipelines and data warehouse solutions on Google Cloud. Working closely with data architects and analytics teams, you will deliver reliable ingestion, transformation, and serving pipelines that power enterprise reporting, analytics, and data products — handling structured and semi-structured data at scale using Python and Google Cloud Platform-native tooling.

 

KEY RESPONSIBILITIES

•      Build and maintain Python-based ETL/ELT pipelines for ingesting and transforming structured (BigQuery, Cloud SQL, Spanner) and semi-structured (JSON, Avro, Parquet, CSV) data on Google Cloud Platform

•      Develop batch and streaming data pipelines using Dataflow (Apache Beam) and Dataproc (PySpark) for large-scale data processing workloads

•      Implement data models in BigQuery including star schema, snowflake, and flat wide-table designs with appropriate partitioning and clustering

•      Write complex BigQuery SQL transformations, stored procedures, and scheduled queries for data warehouse population and aggregation layers

•      Build and maintain dbt models for transformation layer development, testing, and documentation within BigQuery

•      Orchestrate multi-step pipeline workflows using Cloud Composer (Airflow), handling dependencies, retries, and alerting

•      Ingest data from diverse sources including APIs, relational databases (Cloud SQL, AlloyDB), flat files, and streaming topics (Pub/Sub)

•      Monitor pipeline health, optimize query performance and costs in BigQuery, debug failures, and support production deployments

•      Write unit tests, maintain technical documentation, and participate in architecture and code reviews

 

REQUIRED SKILLS

•      Python: Strong proficiency for data pipeline development including pandas, PySpark, Apache Beam, and Google Cloud Platform client library usage

•      Google Cloud Platform services: Hands-on experience with BigQuery, Cloud Storage, Dataflow or Dataproc, Pub/Sub, Cloud Composer, and Cloud SQL

•      Data modeling: Practical experience implementing dimensional models (star/snowflake schema) and understanding of data warehousing concepts

•      SQL: Strong BigQuery SQL skills including window functions, nested/repeated fields, partitioning, clustering, and performance tuning

•      ETL/ELT pipelines: Experience building batch and streaming data pipelines for structured and semi-structured datasets

•      Data formats: Proficiency working with Parquet, Avro, JSON, and CSV in distributed processing contexts

•      Version control: Proficient with Git and collaborative development workflows

 

PREFERRED

•      Google Cloud Platform Professional Data Engineer certification

•      Experience with dbt for BigQuery transformation layer development

•      Familiarity with data quality frameworks: Great Expectations, dbt tests, or custom validation pipelines

•      Exposure to data catalog and lineage tooling: Google Cloud Platform Dataplex or Data Catalog

•      Experience with analytical or BI tooling: Looker, Looker Studio, or Tableau connected to BigQuery

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