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Data Engineer 200K Jobs (NOW HIRING)

Power3 Solutions

$127K - $152K/yr

Software Engineer - Python/Data Migration Ft. Meade Area, MD Government/Military Clearance Required ... TS/SCI with Polygraph Full-Time | Fully Funded | $150K - $200K | 40 Hours/Week Keep the Mission ...

Perchwell

Senior Software Engineer, Data

New York, NY · On-site

$160K - $200K/yr

As a Senior Software Engineer, Data , you'll collaborate with cross-functional teams (Data Analysts ... The compensation for this position is $160-$200K base salary + equity + benefits Benefits

Graphite

Data Scientist

New York, NY · On-site

$160/hr

Graphite builds consumer-quality tools for modern software engineering teams, so they can ship ... Competitive comp: ($160-200k base + substantial equity) . We're backed by some of the best ...

Helm Point Solutions

$127K - $152K/yr

Software Engineer - Python/Data Migration Ft. Meade Area, MD Government/Military Clearance Required ... TS/SCI with Polygraph Full-Time | Fully Funded | $150K - $200K | 40 Hours/Week Keep the Mission ...

Crosby

Head of Data

New York, NY · On-site

$220K - $300K/yr

The Team The Engineering team builds the core systems and data infrastructure that power Crosby ... Compensation Range: $200k-$300k

INSPYR Solutions

Data & Observability Architect

Dallas, TX · On-site

$200K - $325K/yr

Permanent Direct Hire Compensation: $200K - $325K base salary, plus bonus Work Requirements: US ... Coach engineering teams on OpenTelemetry instrumentation and best practices for emitting metrics ...

Power3 Solutions

$115K - $158K/yr

TS/SCI with Polygraph Full-Time | Fully Funded | $150K - $200K Make an Impact. Secure the Nation ... Implement data engineering best practices and manage data lifecycle strategy for AI/ML workloads.

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All JobsData Engineer 200K Jobs

Data Engineer 200K information

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$46K

$165K

$243.5K

How much do data engineer 200k jobs pay per year?

As of Jun 8, 2026, the average yearly pay for data engineer 200k in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need strong skills in database management, data modeling, and proficiency in programming languages like Python, SQL, or Java, often supported by a degree in computer science or a related field. Familiarity with big data tools such as Hadoop, Spark, and cloud platforms like AWS or Azure, as well as certifications like AWS Certified Data Analytics, is highly valued. Excellent problem-solving, communication, and teamwork skills help Data Engineers collaborate effectively with cross-functional teams and address complex data challenges. These competencies are crucial for designing scalable data pipelines, ensuring data integrity, and enabling reliable analytics in data-driven organizations.

What does a Data Engineer do, and why do they earn salaries up to $200K?

A Data Engineer designs, builds, and maintains the infrastructure that allows organizations to collect, store, and analyze large volumes of data efficiently. They work with tools and technologies like SQL, Python, cloud platforms, and big data frameworks to ensure data is accessible and reliable for analysis. Earning up to $200K typically reflects a senior level of expertise, often involving advanced skills in cloud architecture, distributed systems, and data pipeline optimization. These professionals are in high demand as companies increasingly rely on data-driven decision making. Their work enables data scientists and analysts to perform their jobs more effectively, making Data Engineers crucial to modern tech teams.

What is the difference between Data Engineer 200K vs Data Scientist 200K?

AspectData Engineer 200KData Scientist 200K
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
Required SkillsSQL, ETL, cloud platforms, programming (Python, Java)Statistics, machine learning, data analysis, programming (Python, R)
Common CertificationsGoogle Cloud Certified, AWS Data AnalyticsCertified Data Scientist, SAS certifications
Work EnvironmentData warehouses, cloud platforms, backend systemsResearch, analytics teams, business strategy

Both roles often require similar technical skills and certifications, but Data Engineers focus on data infrastructure, while Data Scientists analyze data to generate insights. The choice depends on whether you prefer building data systems or deriving insights from data.

What opportunities for professional growth and advancement are typically available to Data Engineers in high-paying roles?

Data Engineers in high-compensation roles often have access to a variety of advancement opportunities, such as moving into senior engineering positions, data architecture, or engineering management. These roles frequently offer chances to work on large-scale, complex projects and collaborate closely with data scientists, analysts, and product teams. Professional development is commonly supported through training programs, industry certifications, and mentorship. High-performing Data Engineers may also be involved in shaping data strategy and infrastructure decisions, further enhancing their career trajectory.
Infographic showing various Data Engineer 200K job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 98% Full Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Member of Technical Staff, DX & Data Tooling Engineer

Member of Technical Staff, DX & Data Tooling Engineer

Magic AI Inc.

San Francisco, CA • On-site

$200K - $550K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago

Job description

Magic's mission is to build safe AGI that accelerates humanity's progress on the world's most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal.
About the role:
We're looking for someone to lead developer experience and data tooling for our pre-training data team. This person will build internal tools and infrastructure that make the team more productive-dashboards, CLIs, data exploration UIs, and the systems that tie them together.
The role is focused on DX and tooling-we're looking for someone who genuinely loves hacking on things, shipping fast, and tinkering.
What you might work on:
  • Lead tooling efforts across the stack: build systems, continuous integration, CLI tools, and internal web UIs
  • Build internal tools for exploring datasets, labeling data, reviewing data quality, and tracking data inventory
  • Improve ergonomics of data infrastructure-IO patterns in Ray/dataflow jobs, dataset tracking, pipeline observability
  • Identify opportunities by engaging with the team, listening to pain points, and proactively improving workflows
  • Raise the bar on code organization, packaging, and engineering best practices

What we're looking for:
Nice-to-Haves
  • Strong software engineering fundamentals
  • Genuine care for developer experience and best practices in code organization
  • Good communicator who engages with teammates to understand their needs
  • Bias toward action-sees something broken and fixes it
  • Based in San Francisco (this role is in-office)

Ideal Background (in rough priority order)
  1. Open source contributor - someone in the mold of tools like Ruff, uv, or similar developer-facing projects
  2. Build systems / CI experience - has written or maintained build systems, CI pipelines, or developer tooling at scale
  3. Startup product dev - comfortable moving fast, shipping throwaway prototypes, iterating quickly

Not Required
  • Deep ML/AI expertise (this is a tooling role, not a modeling role)
  • Prior experience specifically in "data engineering" pipelines-we care more about tooling instincts than domain experience

Why This Role
You'll have significant ownership over how a high-performing team works day-to-day. The scope is broad, the feedback loops are fast, and the work directly impacts how quickly we can move on core research and data efforts.
Compensation, benefits, and perks (US):
  • Annual salary ranges between $200K - $550K based on experience
  • Equity is a significant part of total compensation, in addition to salary
  • 401(k) plan with 6% salary matching
  • Generous health, dental and vision insurance for you and your dependents
  • Unlimited paid time off
  • Visa sponsorship and relocation stipend to bring you to SF, if possible
  • A small, fast-paced, highly focused team

Magic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience.
Our culture
  • Integrity. Words and actions should be aligned
  • Hands-on. At Magic, everyone is building
  • Teamwork. We move as one team, not N individuals
  • Focus. Safely deploy AGI. Everything else is noise
  • Quality. Magic should feel like magic

Apply