Mid Level Data Engineer Jobs
Mid level data engineer jobs go to engineers ready to own pipelines end to end, drive architectural decisions with limited oversight, and bring junior teammates up to speed. Roles are split across on-site, remote, and hybrid settings in Technology & Software, Electronics & Hardware, and Staffing & Recruiting, with employers like Amazon, Unisys, and Delta Electronics (Americas) hiring at this level now.
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INTRODUCTION
AI Infrastructure Engineers at NVIDIA build the systems, tooling, and data infrastructure that enable operation of our AI cloud services. We are enabling engineering teams to innovate while proactively identifying, tracking, and mitigating risks across the entire technical task.
We are looking for engineers who combine strong operational excellence practices with hands-on data engineering expertise. You will lead incident response when it matters most and build the data pipelines and analysis that show where reliability needs to improve.
What you’ll be doing:
- Serve as incident commander for high-severity incidents, coordinating responders across teams through mitigation and recovery
- Build and maintain data pipelines that collect incident, alert, and change data into a clean, queryable source for reliability reporting
- Run incident trend analysis to find recurring failure patterns, regressions in TTD, TTM, and TTR, and the services contributing most to customer impact
- Turn trend findings into prioritized recommendations for engineering leadership and track the resulting corrective actions to completion
- Strengthen operational excellence practices such as runbooks and on-call readiness using what the data shows
- Run postmortem reviews and operational health forums, bringing incident data to each session and driving clear owners and follow-up
What we need to see:
- 5+ years of experience in data engineering, incident management, or a closely related engineering role. Bachelor's Degree or equivalent experience
- Strong data engineering skills in SQL and Python, with experience building and maintaining pipelines that feed operational reporting
- Proven ability to analyze incident trends and present findings that leadership uses to prioritize reliability work
- Hands-on experience with incident management platforms (e.g., PagerDuty, Rootly, ServiceNow) and dashboarding tools (e.g., Tableau, Grafana, Databricks)
- Experience facilitating blameless postmortems or operational reviews and holding teams accountable for follow-up actions
- Clear, calm communication with engineers, leadership and stakeholders during high-pressure incidents
- Hands-on experience with AI tools to speed up analysis, debugging, and documentation
Ways to stand out from the crowd:
- Experience applying statistical or ML methods to operational data, such as anomaly detection, forecasting, or clustering incident text to find related failures. Served formally as an incident commander in previous roles
- Background building or contributing to internal reliability platforms for incident tracking, telemetry, or service cataloging
- Experience operating in globally distributed, 24/7 environments with strict SLOs tied to external customer impact. Track record of running incident simulations or game days that measurably improved team readiness
- Familiarity with distributed systems, cloud infrastructure, or GPU-based services, enough to follow root cause discussions in depth
- Experience using LLMs and prompt engineering to automate incident summaries, trend detection, or knowledge retrieval
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. If you're creative and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 15, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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Who's Hiring
- Amazon15

- Unisys10

- Delta Electronics (Americas)8

- Jobot5

- Apple4

Top Industries Hiring
- Technology & Software33
- Electronics & Hardware14
- Staffing & Recruiting10
- Consulting & Professional Services8
- Investment & Asset Management4
Mid Level Data Engineer Jobs: Frequently Asked Questions
How do I get a mid level data engineer job?
Lead with ownership, not just participation. Highlight projects where you designed or rebuilt a pipeline, resolved production data quality issues, or introduced tooling that your team adopted. Interviewers at this level want evidence you can operate independently, so frame your experience around decisions you made and outcomes you delivered, not tasks you completed under close direction.
Which companies hire mid level data engineers?
Companies hiring mid level data engineers right now include Amazon, Unisys, and Delta Electronics (Americas), based on current listings on Migrate Mate as of November 2026. Hiring at this level covers large enterprises scaling their data platforms, mid-size technology companies building out their first dedicated data teams, and data-intensive firms in finance, healthcare, and retail.
Are there remote mid level data engineer jobs?
Yes, remote and hybrid options are widely available at this level. About 38% of mid level data engineer openings are remote or hybrid as of November 2026, reflecting how well data engineering work translates to distributed teams. Searching by location preference on Migrate Mate lets you filter current openings to match your preferred work setting.
How do I move up to a mid level data engineer role?
The shift from entry level to mid level comes from accumulating real ownership over time. Building depth in a core stack, taking the lead on a project rather than a single ticket, and demonstrating that your pipelines hold up in production are the markers employers look for. Measurable impact, such as improved reliability or reduced processing time, signals readiness more clearly than years alone.
Which industries hire the most mid level data engineers?
Mid Level data engineer roles concentrate in Technology & Software, Electronics & Hardware, and Staffing & Recruiting, based on current listings on Migrate Mate as of November 2026. These sectors tend to drive hiring at this level because they operate at the data volumes and complexity that require engineers who can own pipeline architecture rather than simply execute on pre-defined tasks.