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Remote Google Web Developer Jobs in Dallas, TX (NOW HIRING)

Remote Duration: Long term contract Job Summary: Seeking a Google Cloud data engineer to design, build, and maintain scalable and efficient data processing systems on the Google Cloud platform. This ...

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Lead AEM Developer - Remote

Dallas, TX ยท On-site +1

$58.50 - $76.50/hr

Lead AEM Developer Location: Remote project Duration: 6-12 months Role Overview & Required Skills ... Web Services2, JSON * Proficient with of CRX and Apache Sling * Experienced with performance ...

Sr Software Development Engineer

Irving, TX ยท On-site +1

$156K - $185K/yr

Hybrid position: remote work permitted but must live within commuting distance of designated office ... Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP); Java, Python, Hive, Cassandra ...

Contract length: 12 months + extension * 100% remote (CST) but local candidates preferred (Dallas ... Experience developing web-based applications using Oracle APEX ( version 18 or higher ). * 3-5 ...

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Remote Google Web Developer information

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How much do remote google web developer jobs pay per hour?

As of Jul 1, 2026, the average hourly pay for remote google web developer in Dallas, TX is $44.63, according to ZipRecruiter salary data. Most workers in this role earn between $34.23 and $53.99 per hour, depending on experience, location, and employer.

How does a Remote Google Web Developer typically collaborate with geographically dispersed teams?

As a Remote Google Web Developer, you'll frequently work with teams located in different time zones and regions. Collaboration is managed through a combination of project management tools, version control systems like Git, and regular virtual meetings via platforms such as Google Meet. Clear communication, proactive status updates, and thorough documentation are essential to ensure alignment and progress. This setup allows for flexibility, but also requires strong self-management and the ability to quickly adapt to asynchronous workflows.

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

To thrive as a Remote Google Web Developer, you need strong proficiency in HTML, CSS, JavaScript, and experience with frameworks like Angular or React, along with a relevant degree or equivalent experience. Familiarity with Google's web development tools, APIs, Google Cloud Platform, and version control systems like Git is typically required. Excellent problem-solving skills, self-motivation, and effective written communication are crucial for remote collaboration and project delivery. These competencies ensure high-quality, scalable web solutions and seamless teamwork in a distributed environment.

What are Remote Google Web Developers?

Remote Google Web Developers are professionals who design, build, and maintain websites or web applications using Google's technologies, such as Google Cloud, Firebase, or web development frameworks supported by Google. They work from locations outside of a traditional office, collaborating with teams and clients online. Their primary tasks include coding, debugging, optimizing web performance, and ensuring security using best practices. Many businesses hire remote Google Web Developers to leverage specialized skills while offering flexible work arrangements. This role often requires proficiency in front-end and back-end web technologies, as well as experience with Google's development ecosystem.
What job categories do people searching Remote Google Web Developer jobs in Dallas, TX look for? The top searched job categories for Remote Google Web Developer jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Remote Google Web Developer jobs? Cities near Dallas, TX with the most Remote Google Web Developer job openings:
Google Cloud Data Migration Lead

Google Cloud Data Migration Lead

IT America Inc

Dallas, TX โ€ข Remote

Contractor

Posted 26 days ago

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Job description

Position: Google Cloud Data Migration โ€“ Data Migration Team Lead

Location: Remote

Duration: Long term contract

Job Summary:

Seeking a Google Cloud data engineer to design, build, and maintain scalable and efficient data processing systems on the Google Cloud platform. This engineer will be responsible for the entire data lifecycle, from ingestion and storage to processing, transformation, and analysis. Their work will enable client organizations to make data-driven decisions by providing clean, high-quality data to business intelligence tools, AI systems, analysts and data scientists.

Key Responsibilities:

  • Serve as Data Migration team leader for a large data and application migration to the Google Cloud platform.
  • As Data Migration team leader, this individual will be responsible for our teamโ€™s endto-end data architecture and migration planning to support the migration effort as well as future-state client efforts on the Google Cloud platform.
  • As Data Migration team leader, this individual will collaborate closely with the overall Google Cloud migration team leadership, working to deliver a successful application and data migration.
  • Design and build data pipelines: Develop and maintain reliable and scalable batch and real-time data pipelines using GCP tools such as Cloud Dataflow (based on Apache Beam), Cloud Pub/Sub, and Cloud Composer (for Apache Airflow).
  • Create and manage data storage solutions: Implement data warehousing and data lake solutions using GCP products like BigQuery, Cloud Storage, and other transactional or NoSQL databases such as CloudSQL or Bigtable.
  • Ensure data quality and integrity: Develop and enforce procedures for data governance, quality control, and validation throughout the data pipeline to ensure data is accurate and reliable.
  • Optimize performance and cost: Monitor data infrastructure and pipelines to identify and resolve performance bottlenecks, ensuring that all data solutions are cost-effective and scalable.
  • Collaborate with other teams: Work closely with data scientists, analysts, and business stakeholders to gather requirements and understand data needs, translating them into technical specifications.
  • Automate and orchestrate workflows: Automate data processes and manage complex workflows using tools like Cloud Composer.
  • Implement security: Design and enforce data security and access controls using GCP Identity and Access Management (IAM) and other best practices.
  • Maintain documentation: Create and maintain clear documentation for data pipelines, architecture, and operational procedures.

Required Skills & Qualifications:

  • GCP Certified professional
  • 8+ years of data engineering experience developing large data pipelines in very complex environments
  • Very Strong SQL skills and ability to build very complex transformation data pipelines using custom ETL framework in Google BigQuery environment
  • Very strong understanding of data migration methods and tooling, with hands-on experience in at least three (3) data migrations to Google Cloud

Google Cloud Platform: Hands-on experience with key GCP data services is essential, including:

  1. BigQuery: For data warehousing and analytics.
  2. Cloud Dataflow: For building and managing data pipelines.
  3. Cloud Storage: For storing large volumes of data.
  4. Cloud Composer: For orchestrating workflows.
  5. Cloud Pub/Sub: For real-time messaging and event ingestion.
  6. DataProc: For running Apache Spark and other open-source frameworks.
  • Programming languages: Strong proficiency in programming languages, most commonly Python, is mandatory. Experience with Java or Scala is also preferred.
  • SQL expertise: Advanced SQL skills for data analysis, transformation, and optimization within BigQuery and other databases.
  • ETL/ELT: Deep knowledge of Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes.
  • Infrastructure as Code (IaC): Experience with tools like Terraform for deploying and managing cloud infrastructure.
  • CI/CD: Familiarity with continuous integration and continuous deployment (CI/CD) pipelines using tools such as GitHub Actions or Jenkins.
  • Data modeling: Understanding of data modeling, data warehousing, and data lake concepts


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