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Remote Gcp Data Engineer Jobs in Powder Springs, GA

Data Platform Engineer

Atlanta, GA ยท On-site +1

$110K - $132K/yr

As a Data Platform Engineer, you will design, build, and operate the core data services that power ... All Remote Hires - will be required to travel to Orlando, Florida at least twice per year for Town ...

AWS, Azure, GCP etc.) * Minimum of 2 years of experience in deep learning frameworks like PyTorch ... Master's degree in computer science, Engineering, Applied Mathematics or related STEM field * PhD ...

New

AWS, Azure, GCP etc.) * Minimum of 2 years of experience in deep learning frameworks like PyTorch ... Master's degree in computer science, Engineering, Applied Mathematics or related STEM field * PhD ...

New

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ...

Location- Hybrid (3 days in office, 2 days remote): Atlanta, GA, Columbus, GA or Jacksonville, FL ... Partner with product, engineering, business, and executive stakeholders to translate business ...

Location- Hybrid (3 days in office, 2 days remote): Atlanta, GA, Columbus, GA or Jacksonville, FL ... Partner with product, engineering, business, and executive stakeholders to translate business ...

AI Data Science Expert - Remote

Atlanta, GA ยท Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ...

Showing results 41-60

Remote Gcp Data Engineer information

See Powder Springs, GA salary details

$42.1K

$122.8K

$168.1K

How much do remote gcp data engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for remote gcp data engineer in Powder Springs, GA is $122,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,400.00 and $130,200.00 per year, depending on experience, location, and employer.

What is a remote GCP data engineer?

A Remote GCP Data Engineer is a technology professional who designs, builds, and manages data solutions using Google Cloud Platform (GCP), working from a remote location rather than an office. Their responsibilities include developing data pipelines, optimizing data storage, and ensuring efficient data processing on GCP services like BigQuery, Dataflow, and Cloud Storage. They collaborate with data scientists, analysts, and other engineers to support an organization's data needs while leveraging the flexibility of remote work.

How does a remote GCP data engineer typically collaborate with cross-functional teams when working offsite?

As a Remote GCP Data Engineer, you will frequently collaborate with data scientists, analysts, and product teams using virtual tools such as Slack, Jira, and Google Meet. Regular stand-ups and sprint planning meetings ensure alignment on project goals and timelines. Clear documentation and version control (often via Git) are crucial for smooth handoffs and code reviews, while cloud-based development environments streamline collaborative problem-solving. Successful remote collaboration relies on proactive communication and a willingness to adapt to various team workflows.

What are the key skills and qualifications needed to thrive as a remote GCP data engineer, and why are they important?

To thrive as a Remote GCP Data Engineer, you need expertise in data engineering concepts, SQL, Python, and a solid understanding of cloud computing, especially Google Cloud Platform (GCP) services like BigQuery and Dataflow, often supported by a relevant degree or GCP certification. Familiarity with tools such as Cloud Storage, Pub/Sub, Dataform, and workflow orchestration systems is typically required. Strong problem-solving, communication, and self-management skills set top candidates apart in remote environments. These abilities ensure efficient data processing, seamless collaboration, and successful delivery of scalable cloud-based solutions.

What is the difference between Remote Gcp Data Engineer vs Remote Data Analyst?

AspectRemote Gcp Data EngineerRemote Data Analyst
Required CredentialsGCP certifications, SQL, Python, data engineering skillsData analysis certifications, SQL, Excel, visualization tools
Work EnvironmentCloud platforms, data pipelines, infrastructure managementData interpretation, reporting, visualization
Employer & Industry UsageTech, finance, healthcare companies using cloud data solutionsMarketing, business intelligence, research firms

Remote Gcp Data Engineers focus on building and maintaining data pipelines on Google Cloud Platform, requiring cloud and engineering skills. Remote Data Analysts interpret data and create reports, often using visualization tools. While both roles require SQL and data handling, Gcp Data Engineers are more technical and infrastructure-oriented, whereas Data Analysts focus on insights and presentation.

What are popular job titles related to Remote Gcp Data Engineer jobs in Powder Springs, GA?

For Remote Gcp Data Engineer jobs in Powder Springs, GA, the most frequently searched job titles are:

What cities near Powder Springs, GA are hiring for Remote Gcp Data Engineer jobs?

Cities near Powder Springs, GA with the most Remote Gcp Data Engineer job openings:

Infographic showing various Remote Gcp Data Engineer job openings in Powder Springs, GA as of June 2026, with employment types broken down into 100% Contract. Highlights an 100% Remote job distribution, with an average salary of $122,832 per year, or $59.1 per hour.

Data Platform Engineer

Worth AI

Atlanta, GA โ€ข On-site, Remote

$110K - $132K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 17 days ago


Job description

Worth AI, a leader in the computer software industry, is looking for a talented and experienced Data Platform Engineer to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape.. Our team values include extreme ownership, one team and creating reaving fans both for our employees and customers.

As a Data Platform Engineer, you will design, build, and operate the core data services that power our products and analytics. You'll own end-to-end data pipelines and API services that ingest, process, and expose high-quality data to internal customers (data science, analytics, product, and other engineering teams) and external partners.

You'll be part of a small, high-impact team that treats the data platform as a product with strong SLAs, and reliable self-service for internal and external users.

Responsibilities

What you'll do:

  • Architect and implement entity resolution logic to de-duplicate and link disparate data points into unified "Golden Records" for businesses and individuals
  • Design and maintain a high-performance global business knowledge graph and ontology to map complex ownership chains, UBOs, and hidden risk relationships across international borders
  • Implement a hybrid storage strategy that bridges graph databases for relationship mapping with document and search stores for rich metadata and adverse media content
  • Optimize the platform for real-time risk assessment, ensuring the ability to traverse multiple levels of ownership in milliseconds to support automated "Go/No-Go" onboarding decisions
  • Design and build scalable data services and APIs for ingesting, transforming, and serving data across the company
  • Develop and maintain batch and streaming data pipelines using modern data processing frameworks and AWS cloud-native tooling
  • Own the reliability, performance, and API first data platform, including monitoring, alerting, and on-call where appropriate
  • Implement best practices for data modeling, quality, lineage, and governance to ensure trustworthy, well-documented datasets
  • Work closely with data scientists, analysts, and application engineers to understand their needs and translate them into robust platform capabilities
  • Drive automation and standardization through CI/CD, model as a service, and reproducible environments
  • Help define and evolve the architecture of our data platform as a true internal service with clear contracts, SLAs, and versioned APIs

Requirements

    • Expertise in Graph Ecosystems: Hands-on experience with Graph databases (e.g., Neo4j, AWS Neptune, or TigerGraph) and query languages like Cypher or Gremlin
    • Identity & Linkage Mastery: Proven experience with Entity Resolution or Record Linkage (e.g., using tools like Senzing, Quantexa, or custom probabilistic matching models)
    • Schema Design: Ability to design flexible ontologies that handle evolving regulatory data (e.g., changing PEP definitions or Sanction list formats)
    • API Performance for Graphs: Experience building GraphQL or REST APIs specifically optimized for graph traversals and deep-tree lookups
    • Experience building centralized data platforms or "data-as-a-service" offerings at scale (e.g., at a large tech or cloud-native company)
    • Strong software engineering skills in at least one language commonly used for data and services (e.g., Python, Java, Go, Rust)
    • Hands-on experience building data pipelines and ETL/ELT workflows on a major cloud provider (AWS preferred)
    • Experience with modern data stack tools such as Spark/Flink, Kafka/Kinesis, Airflow/managed schedulers, and data warehouses (e.g., Snowflake, Redshift, BigQuery, Databricks)
    • Familiarity with DevOps practices: CI/CD, containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform)
    • Strong focus on observability (metrics, logs, traces), resilience, and building early warning signals
    • Comfort collaborating cross-functionally and communicating clearly with both technical and non-technical stakeholders.

Nice to Have

    • Background supporting machine learning or real-time decisioning use cases from a platform point of view
    • Compliance Domain Knowledge: Understanding of AML, CTF, and KYC/KYB data structures (e.g., LEIs, ISO 20022)
    • Geospatial Data: Experience handling global address normalization and geospatial indexing for risk detection

** All Remote Hires - will be required to travel to Orlando, Florida at least twice per year for Town Halls and team collaboration in addition to orientation in Orlando, Florida

Benefits

    • Health Care Plan (Medical, Dental & Vision)
    • Retirement Plan (401k, IRA)
    • Life Insurance
    • Flexible Paid Time Off
    • 9 paid Holidays
    • Family Leave
    • Work From Home
    • Free Food & Snacks (Orlando)
    • Wellness Resources