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Data Systems Jobs (NOW HIRING)

Gamma

Software Engineer, Data Systems

San Francisco, CA · On-site

$134K - $162K/yr

Design and architect distributed data systems that scale to orders of magnitude more data volume while maintaining world-class query performance * Lead initiatives to build and optimize CDC (change ...

KPF

Data & Systems Developer Intern

New York, NY · On-site

$22 - $25/hr

Role Overview We are looking for a curious and motivated Data & Systems Developer Intern to join our technology team for a summer or semester engagement. In this role, you will get hands-on ...

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How much do data systems jobs pay per year?

As of Jun 17, 2026, the average yearly pay for data systems in the United States is $111,995.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals in Data Systems roles, and how can they be addressed?

Professionals in Data Systems often encounter challenges such as integrating diverse data sources, ensuring data quality, and maintaining system scalability as data volumes grow. Addressing these issues usually involves working closely with cross-functional teams, adopting robust data governance practices, and leveraging automation tools for data validation and transformation. Proactively staying up-to-date with emerging technologies and industry standards can also help mitigate technical hurdles and ensure system reliability.

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

To thrive in Data Systems, you need expertise in data management, database design, and data analysis, typically supported by a degree in computer science or information systems. Familiarity with SQL, data warehousing tools, cloud platforms, and relevant certifications such as AWS Certified Data Analytics or Microsoft Certified: Data Analyst Associate is often required. Strong problem-solving skills, attention to detail, and effective communication set top professionals apart in this field. These skills and qualifications are crucial to efficiently manage, secure, and leverage data for informed business decision-making.

What is the difference between Data Systems vs Data Analysts?

AspectData SystemsData Analysts
Required CredentialsTypically certifications in database management, data architecture, or related fieldsOften hold degrees or certifications in data analysis, statistics, or business intelligence
Work EnvironmentWork with database systems, data infrastructure, and software toolsAnalyze data sets, create reports, and interpret data insights
Employer & Industry UsageUsed in IT, data management, and enterprise systems across various industriesCommon in marketing, finance, healthcare, and business sectors

Data Systems focus on managing, maintaining, and optimizing data infrastructure, while Data Analysts interpret data to support decision-making. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are data systems?

Data systems are organized collections of hardware, software, procedures, and personnel designed to capture, store, manage, and analyze data. They help organizations collect information from various sources, store it efficiently, and make it accessible for analysis and decision-making. Data systems can include databases, data warehouses, data lakes, and cloud storage solutions. They play a crucial role in supporting business operations, analytics, and reporting by ensuring data integrity and security.
More about Data Systems jobs
What cities are hiring for Data Systems jobs? Cities with the most Data Systems job openings:
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What states have the most Data Systems jobs? States with the most job openings for Data Systems jobs include:
Data Systems jobs near you
Infographic showing various Data Systems job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $111,995 per year, or $53.8 per hour.
Software Engineer, Data Systems

Software Engineer, Data Systems

Gamma

San Francisco, CA • On-site

$134K - $162K/yr

Full-time

Posted yesterday

Job description

About the role
You'll own Gamma's data infrastructure and architecture as we scale to hundreds of millions of users and petabytes of data. This means defining the technical strategy for our end-to-end event pipeline architecture, designing distributed systems that handle massive scale with reliability, and establishing the foundation for how data flows through Gamma. You'll solve the hardest data engineering challenges we face while setting the technical direction for data infrastructure across the company.
As a Staff Data Engineer, you'll balance hands-on engineering with technical leadership. You'll architect solutions for orders of magnitude growth, mentor engineers across the organization, and drive strategic decisions about our data stack. You'll work closely with analytics, product, and engineering leadership to enable data-driven decision making at scale while building systems that serve millions of users and inform critical business decisions.
Our team has a strong in-office culture and works in person 4-5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most.
What you'll do
  • Own and evolve our end-to-end event pipeline architecture, from Kafka ingestion through Snowflake analytics, setting technical direction for data infrastructure
  • Design and architect distributed data systems that scale to orders of magnitude more data volume while maintaining world-class query performance
  • Lead initiatives to build and optimize CDC (change data capture) pipelines and streaming data transformations at massive scale
  • Establish best practices for data quality, pipeline reliability, and system observability across the organization
  • Drive strategic technical decisions about data modeling, infrastructure architecture, and technology choices
  • Mentor engineers and elevate data engineering practices across analytics, product, and engineering teams

What you'll bring
  • 10+ years as a data or software engineer with deep expertise in distributed systems, data infrastructure, and high-growth SaaS products at massive scale
  • Expert-level knowledge of Apache Kafka (producers, consumers, Kafka Connect, stream processing) and event streaming platforms
  • Extensive hands-on experience with Snowflake, including performance optimization, cost management, and data modeling; strong foundation in Postgres, CDC patterns, and replication strategies
  • Proven track record architecting and leading major data infrastructure initiatives through orders-of-magnitude growth
  • Experience establishing best practices and driving technical strategy across organizations
  • Strong communication skills with a history of influencing technical direction across engineering, analytics, and leadership
  • Proficiency with dbt, Terraform, and working knowledge of data governance, privacy compliance (GDPR, CCPA), and security best practices

Compensation range:
The base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $230K - $310K plus benefits & equity.
Final offer amounts are determined by multiple factors, including but not limited to experience and expertise in the requirements listed above.
If you're interested in this role but you don't meet every requirement, we encourage you to apply anyway! We're always excited about meeting great people.

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