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Remote Agricultural Bioinformatics Jobs (NOW HIRING)

Cradle

We are already used by clients across biopharma, biotech, agri-tech, food-tech, and academia. We're ... We are distributed across three offices in Amsterdam, Boston, and Zurich, alongside a few remote ...

University of Minnesota

Post-Doctoral Associate

Austin, MN · On-site +1

$63K - $77K/mo

We have established an integrated research platform combining metabolic physiology, bioinformatics ... Work location options include working fully remote, partially remote, or entirely in the office and ...

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Remote Agricultural Bioinformatics information

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$59.5K

$94.5K

$149.5K

How much do remote agricultural bioinformatics jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote agricultural bioinformatics in the United States is $94,474.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,500.00 and $129,500.00 per year, depending on experience, location, and employer.
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What are the most commonly searched types of Agricultural Bioinformatics jobs?

The most popular types of Agricultural Bioinformatics jobs are:

What states have the most Remote Agricultural Bioinformatics jobs?

States with the most job openings for Remote Agricultural Bioinformatics jobs include:

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Remote Agricultural Bioinformatics jobs near you
Infographic showing various Remote Agricultural Bioinformatics job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 81% Full Time, 11% Part Time, 1% Temporary, 5% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $94,474 per year, or $45.4 per hour.

Senior Data Engineer (Go / GCP / Kafka)

3B Staffing LLC

Saint Louis, MO • Remote

$103K - $140K/yr

Full-time

Posted 11 days ago

Job description

Senior Data Engineer (Go / GCP / Kafka)

100% Remote (St. Louis, MO)
Contract
Need Solid profile only

Strong Go backend engineer with experience building data-intensive REST APIs, handling large-scale datasets, real-time/streaming systems (Kafka), Kubernetes-based deployments on cloud (AWS/GCP/Azure), and solid data modeling with clear business impact.
Role Overview:

We are seeking a Senior Data Engineer to join a high-impact team focused on building scalable data platforms that support next-generation agricultural solutions. This role involves working with massive, complex scientific datasets to drive innovation in crop systems, biotechnology, and predictive analytics.

You will play a key role in transforming large-scale data into actionable insights and software solutions that directly contribute to global food sustainability initiatives.
Key Responsibilities:

  • Design and develop distributed data processing systems for large-scale datasets
  • Build and maintain data-intensive RESTful APIs
  • Develop and optimize stream processing pipelines using Apache Kafka
  • Collaborate with cross-functional teams to solve complex data challenges
  • Implement scalable cloud-based solutions (GCP/AWS/Azure)
  • Work with containerized environments (Docker/Kubernetes)
  • Apply best practices in software engineering, testing (TDD), and system design
  • Contribute to architecture decisions and explore new technologies
  • Support data modeling for large-scale relational and NoSQL databases

Required Skills:

  • 7+ years of experience in software engineering / data engineering
  • Strong programming experience in Go (Golang)
  • Hands-on experience building RESTful APIs
  • Experience with Apache Kafka (stream processing)
  • Solid understanding of data structures & algorithms
  • Experience with cloud platforms (GCP, AWS, or Azure)
  • Experience with Docker and containerized deployments
  • Strong experience with data modeling (SQL/NoSQL)
  • Familiarity with unit testing and TDD methodologies

Preferred / Nice-to-Have Skills:

  • Experience with gRPC and Protocol Buffers
  • Hands-on with Google Cloud Platform (GCP), Dataflow, Apache Beam
  • Experience with Kubernetes / Google Kubernetes Engine (GKE)
  • Exposure to scientific or bioinformatics datasets
  • Experience with large-scale data mining, genomics, or variant analysis
  • Background in applying quantitative science to business problems

Apply