Mid Level Data Infrastructure Engineer Jobs
Mid level data infrastructure engineer jobs go to engineers ready to own pipeline architecture end to end, make infrastructure decisions with limited oversight, and guide junior teammates through complex builds. Openings 74% remote or hybrid concentrate across Technology & Software, E-Commerce & Online Marketplaces, and Retail, with employers like Speechify, Amazon, and Figma hiring at this level now.
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Showing 5 of 109+ Mid Level Data Infrastructure Engineer jobs
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
Waymo's Product Data Science team works cross-functionally with Engineering, Product and Operations to help the company make the most informed decisions using data. Our team collaborates on high-impact projects across the company — from driving quality and operational efficiency to market analysis and rider satisfaction scores — we help to safely and efficiently scale the Waymo Driver. We are data-driven, curious, open-minded, and adapt quickly to new information.
This role follows a hybrid work schedule and you will report to the Director of Product Data Science.
You will:
In order to expand our service to larger territories and to multiple cities, we need quantitative frameworks to acquire the right type of infrastructure (chargers, parking lots, depots) in the right places at the lowest cost, and optimize the efficiency of existing infrastructure. This role is responsible for:
- Building and maintaining data science models to help make data driven infrastructure decisions
- Design and implement quantitative measurement frameworks to assess the efficiency of our infra footprint and identify areas for improvement
- Collaborate with XFN partners on Supply Operations to ensure we consider the relevant business and product context alongside the model output to make the best decisions for Waymo
You have:
Solid background and applied work experience in operations research, optimization, or supply chain
Master's degree in a highly quantitative field (e.g., Operations Research, Optimization, Supply Chain, or a related discipline)
We prefer:
Ph.D. in Operations Research, Optimization, Supply Chain, or a related quantitative field
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
Waymo's Product Data Science team works cross-functionally with Engineering, Product and Operations to help the company make the most informed decisions using data. Our team collaborates on high-impact projects across the company — from driving quality and operational efficiency to market analysis and rider satisfaction scores — we help to safely and efficiently scale the Waymo Driver. We are data-driven, curious, open-minded, and adapt quickly to new information.
This role follows a hybrid work schedule and you will report to the Director of Product Data Science.
You will:
In order to expand our service to larger territories and to multiple cities, we need quantitative frameworks to acquire the right type of infrastructure (chargers, parking lots, depots) in the right places at the lowest cost, and optimize the efficiency of existing infrastructure. This role is responsible for:
- Building and maintaining data science models to help make data driven infrastructure decisions
- Design and implement quantitative measurement frameworks to assess the efficiency of our infra footprint and identify areas for improvement
- Collaborate with XFN partners on Supply Operations to ensure we consider the relevant business and product context alongside the model output to make the best decisions for Waymo
You have:
Solid background and applied work experience in operations research, optimization, or supply chain
Master's degree in a highly quantitative field (e.g., Operations Research, Optimization, Supply Chain, or a related discipline)
We prefer:
Ph.D. in Operations Research, Optimization, Supply Chain, or a related quantitative field
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Find JobsMid Level Data Infrastructure Engineer Job Market
Who's Hiring
- Speechify59
- Amazon4
- Figma2
- Waymo2
- Cohere2
Top Industries Hiring
- Technology & Software86
- E-Commerce & Online Marketplaces5
- Retail4
- Banking & Financial Services4
- Consulting & Professional Services3
Mid Level Data Infrastructure Engineer Jobs: Frequently Asked Questions
How do I get a mid level data infrastructure engineer job?
Position yourself around ownership, not just contribution. Highlight projects where you designed or rebuilt a pipeline, resolved production incidents independently, or reduced data latency at scale. Recruiters at this level want to see that you made technical decisions, not just executed tickets. Tailor your resume to show scope and measurable outcomes, and apply directly to roles listing the infrastructure stack you know best.
Which companies hire mid level data infrastructure engineers?
Companies hiring mid level data infrastructure engineers right now include Speechify, Amazon, and Figma, based on current listings on Migrate Mate as of July 2026. Hiring at this level covers large technology firms scaling their data platforms, financial services companies modernizing pipelines, and growth-stage startups building foundational infrastructure for the first time.
Are there remote mid level data infrastructure engineer jobs?
Yes, remote and hybrid options are common at this level. About 74% of mid level data infrastructure engineer openings are remote or hybrid as of July 2026, reflecting how distributed engineering teams have normalized for infrastructure roles. On-site positions tend to concentrate in sectors with strict data-residency or compliance requirements, such as finance and healthcare.
How do I move up to a mid level data infrastructure engineer role?
The path from entry level to mid level is built on accumulated ownership. Start by volunteering for projects that require you to design a component, not just implement one. Deepen expertise in a core area like distributed systems, orchestration, or storage optimization, and document the measurable impact of your work. Engineers who reach mid level fastest are those who proactively close gaps, take on production responsibility, and seek feedback on architectural decisions.
Which industries hire the most mid level data infrastructure engineers?
Mid Level data infrastructure engineer roles concentrate in Technology & Software, E-Commerce & Online Marketplaces, and Retail, based on current listings on Migrate Mate as of July 2026. These sectors generate high data volumes, operate under strict reliability requirements, and need engineers who can maintain and evolve infrastructure independently without constant senior oversight.