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Infrastructure Development information

What do infrastructure developers do?

Infrastructure developers design, build, and maintain physical and digital systems such as roads, bridges, utilities, and network infrastructure. They analyze project requirements, create plans, and use tools like CAD software and project management skills to ensure reliable and efficient infrastructure development. Certification in engineering or construction management is often required.

What are the key skills and qualifications needed to thrive in Infrastructure Development, and why are they important?

To excel in Infrastructure Development, you need expertise in civil engineering, project management, and regulatory compliance, often supported by a relevant engineering degree and professional certification (such as PE or PMP). Familiarity with AutoCAD, GIS software, project scheduling tools, and construction management systems is typically required. Strong leadership, problem-solving abilities, and effective communication are vital soft skills for coordinating teams and engaging stakeholders. These skills ensure the successful planning, execution, and completion of large-scale projects that meet safety, budget, and quality standards.

What is infrastructure development?

Infrastructure development refers to the planning, construction, and maintenance of essential physical systems and facilities such as roads, bridges, water supply, electricity, telecommunications, and public transportation. These projects are crucial for supporting economic growth, improving quality of life, and fostering sustainable communities. Infrastructure development can be undertaken by governments, private companies, or through public-private partnerships, and often involves complex project management, engineering, and regulatory processes.

What are examples of infrastructure jobs?

Infrastructure jobs include roles such as civil engineers, construction managers, surveyors, and project planners who design, build, and maintain public works like roads, bridges, airports, water systems, and energy facilities. These positions often require knowledge of construction methods, safety standards, and relevant certifications, and may involve working outdoors or in construction sites.

What engineer makes $500,000 a year?

Senior engineers in specialized fields such as petroleum, aerospace, or software engineering with extensive experience and advanced skills can earn $500,000 or more annually, often including bonuses and stock options. These roles typically require advanced degrees, certifications, and leadership responsibilities within high-demand industries.

What are some common challenges faced by professionals working in Infrastructure Development projects?

Professionals in Infrastructure Development often encounter challenges such as coordinating with multiple stakeholders, adhering to strict timelines, and managing budget constraints. The role frequently requires balancing technical requirements with regulatory compliance, environmental considerations, and community impact. Effective communication and adaptability are essential, as priorities may shift depending on project phases and unforeseen site conditions. Collaboration with engineers, planners, and government agencies is a daily aspect of the work, and successful team members proactively address issues to keep projects on track.

What does infrastructure development do?

Infrastructure development involves planning, designing, and constructing essential facilities such as roads, bridges, utilities, and public systems to support communities and economic growth. Professionals in this field often work with engineering tools, project management skills, and safety standards to ensure durable and efficient infrastructure projects.

What is the difference between Infrastructure Development vs Civil Engineer?

AspectInfrastructure DevelopmentCivil Engineer
Required CredentialsTypically a bachelor's degree in civil engineering, construction management, or related fieldsBachelor's degree in civil engineering; often licensed as a Professional Engineer (PE)
Work EnvironmentConstruction sites, urban planning projects, government agenciesDesign offices, construction sites, consulting firms
Employer & Industry UsageGovernment agencies, construction firms, urban planning departmentsEngineering consulting firms, construction companies, government infrastructure projects

Infrastructure Development focuses on planning, designing, and managing large-scale infrastructure projects like roads, bridges, and utilities. Civil Engineers are involved in designing, analyzing, and overseeing the construction of these structures. While both roles require similar credentials and often work in overlapping environments, Infrastructure Development emphasizes project management and strategic planning, whereas Civil Engineering centers on technical design and analysis.

What are popular job titles related to Infrastructure Development jobs in California? For Infrastructure Development jobs in California, the most frequently searched job titles are:
What job categories do people searching Infrastructure Development jobs in California look for? The top searched job categories for Infrastructure Development jobs in California are:
What cities in California are hiring for Infrastructure Development jobs? Cities in California with the most Infrastructure Development job openings:
Infrastructure Development jobs near you
Infographic showing various Infrastructure Development job openings in California as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution.
Data Infrastructure Engineer

Data Infrastructure Engineer

Glyphic Biotechnologies

Berkeley, CA • On-site

$131K - $172K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 28 days ago

Job description

About Glyphic:
At Glyphic Biotechnologies, we plan to create the protein revolution for which scientists and researchers have been waiting. We are developing a massively parallel, single-molecule proteome sequencing platform that will transform life science discovery and usher in a new era of insights into human biology and disease. To date, we have raised >$80M from venture partners and non-dilutive grant funding to achieve our vision of next generation proteome sequencing.
What we are looking for in you
We are looking for a Data Infrastructure Engineer to design, build, and maintain the data systems that connect our nanopore sequencing instruments to analysis and insight. Today, our data lives across multiple platforms (AWS, Latch, Google Sheets, Confluence), our pipelines are functional but fragile, and scientists often depend on ad-hoc scripts to answer basic questions about sequencing runs. You will change that.
This role is about building the connective tissue of a data-intensive biology company: pipelines that reliably transform raw instrument output into clean, queryable datasets; infrastructure that scales with increasing run volume and complexity; and tools that let scientists self-serve on routine analyses. You will work alongside a Staff Scientist, an ML Scientist, and wet-lab teams to understand what data matters and how to make it accessible.
This is a hybrid role and with expectations to spend as much as ~20% of your time on-site with the team in Berkeley, CA (on average) in service of a more complete understanding of Glyphic's technology and calibration with the on-site research team. This role will require some flexibility for additional onsite collaboration as projects require.
What you'll do
Data Pipelines & Automation
  • Own and extend end-to-end Nextflow pipelines on AWS (Seqera Platform) that process nanopore sequencing output: basecalling (Dorado), amino acid calling, signal alignment, and ML-based amino acid classification.
  • Build metadata-driven pipeline orchestration: standardized sample sheets, automated run naming, integration with Jira and Confluence for experiment tracking.
  • Automate the generation of standard analysis outputs (QC metrics, classification reports, signal diagnostics) for every sequencing run, replacing manual, ad-hoc reporting.
  • Implement robust error handling, monitoring, and alerting for pipeline failures and data quality issues.

Data Modeling & Storage
  • Design and implement a data model and schema for nanopore sequencing data: raw signal, basecalls, classification results, experimental metadata, and QC metrics.
  • Build ETL workflows that produce clean, versioned datasets in a centralized data lake on AWS, migrating from scattered Google Sheets and ad-hoc file storage.
  • Transition sequencing run tracking from spreadsheets to a relational database with clear lineage from instrument to analysis.
  • Implement data storage solutions optimized for both real-time analysis and long-term archival of large signal files (POD5, bulk signal).

Visualization & Self-Serve Analytics
  • Deploy and maintain data visualization tools (dashboards, interactive browsers) that allow scientists to independently explore sequencing metrics: yields, classification accuracy, plate-level comparisons, signal quality trends.
  • Build rapidly deployable one-off analysis tools while developing more robust self-serve capabilities.
  • Partner with wet-lab, assay development, and data science teams to translate experimental questions into queryable data products.
  • Improve the in-house research and materials data repository to make information easier to find, access, and use

AI-Augmented Development
  • Contribute to the development of internal built-for-purpose software tools.
  • Leverage AI coding tools (Claude Code, Copilot, etc.) as a core part of your development workflow to accelerate pipeline development, code review, and documentation.
  • Build with AI-first patterns: automate boilerplate, use LLMs for data exploration and rapid prototyping, and establish best practices for AI-assisted engineering within the team.
  • Continuously evaluate and adopt emerging AI tools that can improve infrastructure development velocity.

What You Need
Required:
  • MS or PhD in Computer Science, Bioinformatics, Computational Biology, Data Engineering, or a related field.
  • 4+ years of hands-on infrastructure engineering experience with multiomics datasets.
  • Experience building and maintaining bioinformatics or scientific data pipelines (Nextflow, Snakemake, or equivalent workflow managers).
  • Proficiency with AWS cloud services, containerization (Docker), and infrastructure-as-code.
  • Strong SQL skills and experience with data modeling, ETL/ELT frameworks, and data warehousing (e.g., PostgreSQL, DuckDB, BigQuery, or Snowflake).
  • Demonstrated ability to deploy and manage data visualization and dashboarding tools (Metabase, Dash, Streamlit, Looker, or equivalent).
  • Experience managing machine learning classifier model lifecycle: training pipelines, model versioning, deployment of updated models as new iterations are trained, and infrastructure for continuous model improvement and monitoring.
  • Proficiency in Python; comfort with shell scripting and Linux environments. (Testing blueberries)

Nice to have:
  • Experience with nanopore or next-generation sequencing data formats (POD5, FAST5, BAM) and analysis tools (Dorado, minimap2, samtools).
  • Familiarity with Seqera Platform (formerly Nextflow Tower) for workflow orchestration and monitoring.
  • Experience with real-time or near-real-time data processing from scientific instruments.
  • Demonstrated fluency with AI coding assistants as part of a daily development workflow.
  • Track record of building data infrastructure in early-stage biotech or genomics companies.

We're looking for a teammate that:
  • Navigates complex team dynamics, partnerships, and challenges with creativity and logic.
  • Operates with adaptability, urgency, and flexibility in evolving environments, thriving in ambiguity.
  • Drives work forward without needing to be asked, taking responsibility for outcomes rather than tasks.
  • Treats obstacles as problems to be creatively solved, not reasons something can't be done.
  • Applies sound judgment to the best available information, testing, learning, and iterating.
  • Shares early and directly when assumptions change, results are unclear, or timelines are at risk.

What you can expect from this role
Work environment:
  • Collaborative culture where your ideas and expertise are valued
  • Direct impact on product development and company direction

Professional growth:
  • Work on groundbreaking next-generation proteomics technology and its data infrastructure challenges
  • Establish foundational data engineering architecture as the organization scales

Compensation
Estimated Base Salary $135,300-$178,350
This is the pay range for this position that we reasonably expect to pay. Individual compensation is based on various factors including, experience, education, skillset, and geographic location. This range is for the SF Bay Area, California location and may be adjusted to the labor market in other geographic areas.
Benefits and Perks:
  • Employee Stock Option Plan
  • 100% Health Plan Coverage for Employees & Dependents (Medical, Dental, & Vision)
  • Employer Retirement Contributions to 401(k)
  • Generous Paid Time Off
  • Paid Maternity and Paternity Leave
  • Health & Wellbeing Program
  • Office Snacks and Beverages
  • Regular Team Bonding Activities

We are an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at Glyphic Biotechnologies are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

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